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[null,null,"List of collaborators"]
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[null,null,"Name","Company","Language","e-mail"]
[null,1,"John Mulhausen","3M","Concepteur original","jrmulhausen2@mmm.com"]
[null,2,"Daniel Drolet","IRSST","Co-Concepteur","daniel.drolet@sympatico.ca"]
[null,3,"Perry Logan","3M","EASC Committee","pwlogan1@mmm.com"]
[null,4,"André Dufresne","McGill University","Co-Concepteur","andre.dufresne@mcgill.ca"]
[null,5,"Jérôme Lavoué","IST Lausanne +41 21 314 74 21","Co-Concepteur","jerome.lavoue@hospvd.ch"]
[null,6,"Julietta Rodriguez","Profesora Asistente Salud Ocupacional Universidad El Bosque - Colombia","Spanish translation","juliettarodriguez@videotron.ca"]
[null,7,"Raffaella Bruzzi","IST Lausanne","Italian translation"]
[null,8,"Catherine Tomicic","IST Lausanne: +41 21 314 74 21","German translation","Catherine.Tomicic@hospvd.ch"]
[null,9,"Wilson N. Holiguti","3M do Brasil Tel. (19) 3838-7255","Portuguese translation","wnholiguti@mmm.com"]
[null,10,"Yonghua He","Fundan University, Shanguai","Chinese translation","hyhup@shmu.edu.cn"]
[null,11,"Zdeněk Fiala","Faculty of Medicine in Hradec Kralove, Institute of Hygiene and Preventive Medicine","Czech translation","Fiala@lfhk.cuni.cz"]
[null,12,"Shrenik Ranpura","3M india","Hindi translation","smranpura@mmm.com "]
[null,13,"Tom Geens","Belgian Society of Occupational Hygiene","Dutch translation","tom.geens@bsoh.be"]
[null,14,"Jooyeon Hwang","Environmental Health Sciences\nSchool of Public Health, University of Minnesota","Korean Translation","hwang100@umn.edu / jooyeonh@gmail.com"]
[null,15,"Hans Thore Smedbold ","Proactima","Norwegian Translation","Hans.Thore.Smedbold@proactima.com"]
[null,16,"Taner PAMUK\nArzu FIRLARER",null,"Turkish translation","tanerpamuk@gmail.com\nafirlarer@gmail.com"]
[null,17,"Kateryna Zhylenko"," Water Associates\nOccupational Hygiene and Safety\n(T) (613) 839-3053  (C) (613) 294-1255\n","Russian translation","Kateryna Zhylenko <kzhylenko@envireau.ca>"]
[null,18,"Haruo Hashimoto, CIH","Industrial Hygiene Manager, MOH\nEMG Marketing GK (formerly, ExxonMobil YK, Japan)\nPhone: 81-3-5495-6433  Fax: 81-3-5495-6541\nCellular: 81-80-2009-4627","Japanese translation","Hashimoto, Haruo <haruo.hashimoto@tonengeneral.co.jp>"]
[null,19]
[null,20]
[null,21]

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[null,"The material embodied on this software is provided \"as-is\" and without warranty of any kind, expressed, implied or otherwise, including without limitation any warranty of merchantability or fitness for a particular purpose.\n",null,3,"INTRO","The material embodied on this software is provided \"as-is\" and without warranty of any kind, expressed, implied or otherwise, including without limitation any warranty of merchantability or fitness for a particular purpose.\n","El material incorporado en este software se provee \"tal-cual\", sin garantía de ninguna clase, expresa, implícita u otra, incluyendo sin limitación cualquier garantía para mercadeo o propiedad para un propósito particular.\n","Le matériel inclus dans ce logiciel est fourni \"tel quel\" sans aucune garantie, mentionnée, implicite ou autre, incluant sans limitation toute garantie sur la valeur marchande ou l'utilisation pour une application particulière.\n","Das Material dass in dieser Software enthalten ist, ist ohne Mängelgewähr geliefert, ohne jene Gewährleistung, erwähnt, gesetzlich, oder ansonsten, einschliesslich ohne Begrenzung jene Zusicherung allgemeiner Gebrauchstauglichkeit oder jene Gewährleistung der Eignung für einen bestimmten Zweck.\n","Il materiale presentato  in questo software é fornito \"cosi' com'é\" senza alcuna garanzia esplicita o implicita, incluse garanzie di commerciabilità, adeguatezza all'uso e legalità di qualsiasi servizio fornito.\n","该软件中的内容是以“依照原样”的形式提供的，不提供任何明确的、隐含的或其他形式的担保，包括但又不局限于用于某种特殊目的任何商业的或者适应性的担保\n","O material contido neste software é fornecido \"tal qual\" e sem garantia de qualquer espécie, expressa, implícita ou outra, incluindo sem limitação de qualquer garantia de comercialização ou adequação para um uso particular.\n","Materiál zahrnutý v tomto softwaru je poskytován tak \"jak je\" bez jakékoli záruky vyjádřené, vyplývající nebo jiné a bez omezení jakékoliv záruky obchodovatelnosti nebo vhodnosti pro určitý účel.\" \n","इस सोफ्टवेयर में संनिहित सामग्री 'यथास्थिति' तथा किसी भी प्रकार की व्यक्त, निहित या अन्यथा वारंटी के बगैर दी गई है और व्यापारिकता या विशेष उट्ठेश्य के लिए उपयुक्तता की कोई वारंटी की किसी परिसीमा के बगैर दी गई है.\n","Het materiaal in deze software wordt geleverd \"zoals het is\" en zonder enige vorm van garantie, noch expliciet, noch impliciet of anders, inbegrepen maar niet gelimiteerd door enige garantie van verkoopbaarheid of geschiktheid voor specifieke doeleinden.\n","이 소프트웨어에 포함된 자료는 어떠한 보증없이 즉, 특정 목적에 대한 상용화나 적합성의 보증에 제한없이 \"그대로\" 제공, 표현, 내포되었습니다.","Materialet nedfelt på denne programvaren leveres \"som den er\" og uten garanti av noe slag, uttrykt, underforstått eller på annen måte, inkludert, uten begrensning alle garantier om salgbarhet eller egnethet for et bestemt formål.\n","Bu yazılımın mevcut içeriği ile herhangi bir ticari sınırlama garantisi olmadan \"olduğu gibi\" garanti kapsamı dışındadır, ve kullanım maksadına yönelik olarak yapılan işleme dair uygunluk garantisi içermez.\n\n","Материал, использованный для разработки этой программы, предоставлен для Вашего пользования, \"как есть\" и без каких-либо гарантий, включая, без ограничения, любые гарантии продажи или пригодности для специальных целей.","このソフトウエアに備わった機能は「その状態のままで」提供されるものであり，それが明記されているかどうかに関わらず，有償販売に値するかや特定の用途に適合するか等，いかなる種類の保障の対象にならない．",{"$nulls":3},224,222,228,296,212,73,224,198,213,{"$f":"LEN(O6)","v":255},80,230,208,218,98,{"$f":"LEN(U6)","v":0}]
[null,"In no event shall John R. Mulhausen, Ph.D., CIH, or the American Industrial Hygiene Association (AIHA) be liable for any direct, indirect, special, incidental, or consequential damages of any kind, or any damages whatsoever, including without limitation loss of profit, loss of use, savings or revenue, or the claims of third parties, whether or not John Mulhausen or the AIHA has been advised of the possibility of such loss, however caused, and on any theory of liability, arising out of or in connection with the possession, use, or performance of this software.",null,3.1,"INTRO","In no event shall John R. Mulhausen, Ph.D., CIH, or the American Industrial Hygiene Association (AIHA) be liable for any direct, indirect, special, incidental, or consequential damages of any kind, or any damages whatsoever, including without limitation loss of profit, loss of use, savings or revenue, or the claims of third parties, whether or not John Mulhausen or the AIHA has been advised of the possibility of such loss, however caused, and on any theory of liability, arising out of or in connection with the possession, use, or performance of this software.","En ningún evento, John R. Mulhausen, Ph.D., CIH, o la Asociación Americana de Higiene Industrial (American Industrial Hygiene Association AIHA) son responsables de cualquier daño causado en forma directa, indirecta, especial, fortuito, inmateriales de cualquier clase, o cualquier tipo de daño, incluyendo y sin limitación las pérdidas de ganancia, pérdida de aplicaciones, ahorros o rentas, o los reclamos de terceros, bien sea que John Mulhausen o la AIHA hayan o no advertido sobre la posibilidad de tales pérdidas de alguna manera causadas, y bajo alguna teoría de responsabilidad que surja o en conexión con la posesión, uso, o ejecución de éste software.","Sous aucune circonstance, John R. Mulhausen, Ph.D., CIH ou l'American Industrial Hygiene Association (AIHA) ne peut être tenu responsable de dommages directs, indirects, spéciaux, fortuits ou immatériels de toute nature, incluant sans limitation toute perte de profit, d'utilisation, d'épargne ou de revenu ou toute réclamation d'une tierce partie, que John Mulhausen ou l'AIHA ait été informé ou non de la possibilité d'une telle perte, de quelque manière causée et sur toute théorie de responsabilité résultant de ou en lien avec la possession, l'utilisation ou la performance de ce logiciel.","In keinem Fall soll John R. Mulhausen, Ph.D., CIH, oder die \"American Industrial Hygiene Association\" (AIHA) schadenersatzpflichtig sein, sei es für direkte, indirekte, sonderliche, beiläufig entstandene, folgerichtige Schaden jener Art, oder jene mögliche Schaden, einschliesslich ohne Begrenzung jener Verlust an Gewinn, an Gebrauch, an Ersparnis oder an Einkommen, oder die Schaden Dritter, ob John Mulhausen oder die AIHA von der Möglichkeit eines derartigen Verlusts benachrichtigt wurde oder nicht, wie auch immer verursacht, und von jener Haftpflichttheorie, folgend oder verbunden mit dem Besitz, dem Gebrauch oder der Leistung dieser Software.","In nessun caso, John R. Mulhausen, Ph.D., CIH o l'American Industrial Hygiene Association (AIHA) possono essere ritenuti responsabili di qualsiasi danno diretto, indiretto, speciale, incidentale o consequenziale, o di altra natura, ivi compresa, senza alcuna limitazione, la perdita di profitto, di usabilità, di guadagno o reclami da parte di terzi, anche nel caso in cui John Mulhausen o l'AIHA siano stati preavvisati della possibilità di tali danni, in qualche maniera derivanti dall'utilizzo o la performance di questo software.","不论John R. Mulhausen, Ph.D., CIH还是美国工业卫生协会（AIHA）是否已经建议了如下方面的可能的损失，在任何情况下，John Mulhausen或者美国工业卫生协会都不应承担任何直接，间接，特殊，偶然，或附带的损害责任，或者任何损失，包括所有的利润减少，无法使用，无法保存或者无法获利，或者第三方的声明的责任 来自或者同该软件的拥有，使用或者运行有关导致的任何责任。","Em nenhum caso, John R. Mulhausen, Ph.D., HIC, ou a American Industrial Hygiene Association (AIHA) serão responsabilizados por quaisquer danos diretos, indiretos, acidentais, consequenciais ou de qualquer outra natureza, Ou quaisquer danos, incluindo os sem limitação de perda de lucros, perda de uso, de poupança ou receita, ou créditos de terceiros, tenham sido ou não John Mulhausen ou a AIHA avisados da possibilidade de tais perdas, no entanto causados, bem como em qualquer tese de responsabilidade, decorrentes ou relacionadas com a posse, uso ou desempenho do software. ","John R. Mulhausen, Ph.D., CIH a American Industrial Hygiene Association (AIHA) nejsou v žádném případě odpovědní za  přímé, nepřímé, zvláštní, náhodné nebo následné škody jakéhokoli typu nebo jakékoli jiné škody, včetně neomezených ztrát zisku, ztrát užití, úspor nebo tržeb nebo nároků třetích stran, ať již byli nebo nebyli John Mulhausen nebo American Industrial Hygiene Association (AIHA) zpraveni o možnosti takové ztráty, jakkoli způsobené, a za žádnou teorii odpovědnosti, vyplývající z nebo ve spojitosti s tímto vlastnictvím, užitím nebo interpretací tohoto softwaru.","किसी भी अवस्था में किसी पकार की प्रत्यक्ष, परोक्ष, विशेष, आकस्मिक या परिणामी हानि के लिए जॉन आर. मुलहसन, पीएच. डी., सीआईएच या अमरिकन इन्डस्ट्रियल हाइजिन एसोसिएशन (एआईएचए) उत्तरदायी नही होंगे, या अन्य किसी रीति से हुई हानि जिसमें लाभ की हानि, प्रयोग की हानि, बचत या राजस्व या किसी तीसरे पक्षके दावे भी सम्मिलित हैं, चाहे जान मुलहसन या एआईएचए ने ऐसी हानि की संभावनाओं को सूचित किया हो या नहीं. हानि चाहे किसी भी रीति से हुई हो तथा इस सोफ्टवेयर को लगाने, उपयोग करने या उसके निष्पादन के संबंध में खडी होनेवाली किसी भी देयताओं की थियरी पर जॉन आर. मुलहसन, पीएच. डी., सीआईएच या अमरिकन इन्डस्ट्रियल हाइजिन एसोसिएशन (एआईएचए) उत्तरदायी नही होंगे,","In geen geval zal John R. Mulhausen, Ph.D., CIH, of de Amerikaanse Industriële Hygiëne Associatie (AIHA) aansprakelijk zijn voor enige directe, indirecte, speciale, incidentele of gevolgschade, of enige andere schade, inbegrepen maar niet gelimiteerd door winstderving, verlies van gebruik, besparingen of inkomsten, of de vorderingen van derden, ongeacht of John Mulhausen of de AIHA op de hoogte gesteld werden van de mogelijkheid van dergelijke schade, ongeacht de oorzaak, en in verband met enige theorie omtrent aansprakelijkheid als gevolg van of in verband met het bezit, gebruik of de prestaties van deze software. ","John R. Mulhausen, Ph.D., CIH 혹은 미국산업위생협회에서는 이 소프트웨어를 소유하거나 사용 또는 실행함으로써 어떻게 발생했던 어떠한 법적 책임이 있는지와 관련한 사실을 사전에 인지하고 있었는지 아닌지의 여부와 관계없이 그 어떠한 경우에도 John R. Mulhausen 혹은 미국산업위생협회에서는 직접적, 간접적, 특별한 경우, 우발적인 경우, 또는 결과적으로 생긴 어떤 종류의 손상, 또는 무제한적인 이윤의 손실, 사용불가능 하게 된 것, 수익이나 수입, 또는 제3자의 요구 등을 포함한 어느 손상에도 책임을 지지 않습니다.\n","Under ingen omstendigheter skal John R. Mülhausen, Ph.D., CIH, eller den Amerikanske Yrkeshygiene Foreningen (AIHA) kunne stilles til ansvar for eventuelle direkte, indirekte, spesielle, eller tilfeldige følgeskader av noe slag, eller enhver skade, inkludert uten begrensning til, tap av fortjeneste, tap av bruk, sparing eller inntekter, eller krav fra tredjeparter, hvorvidt John Mülhausen eller AIHA har blitt informert om muligheten for slike tap, uansett årsak, og på enhver teori om erstatningsansvar, som oppstår ut fra eller i forbindelse med besittelse, bruk eller ytelse av denne programvaren.","Hiçbir durumda John R. Mulhausen, Ph.D., CIH, ya da Amerikan Endüstriyel Hijyen Birliği (AIHA) her türlü doğrudan, dolaylı, özel, rastlantısal veya dolaylı zararlardan, ya da herhangi bir kısıtlama olmadan kar kaybı, kullanım kaybı, tasarruf veya gelirden, üçüncü şahısların şikayetlerinden sorumlu tutulamaz. John Mulhausen veya AIHA böyle bir kayıp olasılığını önceden bildirilmiş olsa da olmasa da bu yazılımı bulundurmaya, kullanmaya ve performansına bağlı olarak doğan yükümlülüklerden sorumlu değildir. ","Ни в коем случае Джон Р. Мюльхаузен, доктор философии и сертифицированный промышленный гигиенист, или Американская ассоциация промышленной гигиены (AIHA) не несет ответственности за: 1. любые прямые, косвенные, специальные или случайные убытки любого рода, 2. любой ущерб, включая без ограничений потерю сбережений или дохода, 3. претензии третьих лиц, даже если Джон Мюльхаузен или AIHA были предупреждены о возможности такого ущерба ,возникающего в результате, или в связи с владением, использованием или работой данного программного обеспечения.","John R. Mulhausen, Ph.D., CIH, およびAmerican Industrial Hygiene Association (AIHA) は，このソフトウエアの所有，使用，または性能に起因しまたは関連して発生した利益，機能，預金，収入のその金額に関わらない逸失、および第3者からの要求を含むあらゆる直接的，間接的，特定の，偶発的，結果的な損害に関して，John MulhausenとAIHAがそのような損害の可能性を通知されたかどうかに関わらず，いかなる場合にも責任を負わない．",{"$nulls":3},565,660,594,652,533,197,578,576,636,{"$f":"LEN(O7)","v":623},307,603,509,548,251,0]
[null,0,null,3.2,"INTRO",{"$nulls":18},0,0,0,0,0,0,0,0,0,{"$f":"LEN(O8)","v":0},0,0,0,0,0,0]
[null,0,null,3.3,"INTRO",{"$nulls":18},0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
[null,{"$f":"Translation(D10,trad,Language)","v":"IHSTAT+ : v. 240, 2023"},null,3.4,"INTRO","IHSTAT+ : v. 240, 2023","HIStat+ : v. 240, 2023","IHStat+ : v. 240, 2023","IHSTAT+ : v. 240, 2023","IHSTAT+ : v. 240, 2023","IHSTAT+ : v. 240, 2023","IHSTAT+ : v. 240, 2023","IHSTAT+ : v. 240, 2023","IHSTAT+ : वर्जन. 240, 2023","IHSTAT+ : v, 240, 2023","IHSTAT+ : 버젼 240, 2023","IHSTAT+ : v 240, 2023","IHSTAT+ : v. 240, 2023","IHSTAT+ : версия 240, 2023","IHSTAT+： v. 240, 2023",{"$nulls":3},22,22,22,22,22,22,22,22,26,22,22,21,22,26,21,0]
[null,"Industrial Hygiene Statistics ",null,4,"Titre","Industrial Hygiene Statistics ","Estadísticas de Higiene Ocupacional","Statistiques en hygiène du travail","Statistiken in der Arbeitshygiene","Elementi di statistica in igiene industriale","工业卫生统计","Estatísticas de Higiene Industrial","Statistiky průmyslové hygieny","औद्योगिक स्वास्थ्य सांख्यिकी","Arbeidshygiënische Statistiek","산업 위생 통계","Statistikk for yrkeshygienikere","Endüstriyel İş Hijyeni İstatistikleri","Ститистика промышленной гигиены","産業衛生統計ツール",{"$nulls":3},30,35,34,33,44,6,34,29,28,29,8,31,37,31,9,0]
[null,"Occupational Exposure Limit",null,5,"Titre","Occupational Exposure Limit","Valor Límite de Exposición Ocupacional (OEL)","Valeur limite d'exposition professionnelle","Maximale Arbeitsplatz-Konzentration","Valori limite d'esposizione professionale","职业接触限值","Limite de exposição ocupacional","Pracovní expoziční limit","व्यावसायिक  एक्सपोजर सीमा","Grenswaarde voor Beroepsmatige Blootstelling","직업 노출 기준","Yrkeshygieniske grenseverdi (YGV)","Mesleki Maruziyet Limiti (OEL)","Лимит профессионального облучения (ЛПО)","ばく露限界値",{"$nulls":3},27,44,42,35,41,6,31,24,25,44,8,33,30,39,6,0]
[null,"Sample data",null,6,"Titre","Sample data","Datos","Données","Daten","Dati ","样品数据","Dados da amostra","Vzorky","नमूना डाटा","Steekproefgegevens","표본 데이터","Måledata","Örnek veri","Данные выбороки","サンプル値",{"$nulls":3},11,5,7,5,5,4,16,6,10,18,6,8,10,15,5,0]
[null,"OEL",null,7,"Titre","OEL","LEO  o OEL","VLE","MAK","OEL ","OEL","LEO","EL","ओईएल - व्यावसायिक  एक्सपोजर सीमा","GBB","직업 노출 기준","YGV","OEL","ЛПО","ばく露限界値",{"$nulls":3},3,10,3,3,4,3,3,2,32,3,8,3,3,3,6,0]
[null,"Descriptive statistics",null,8,"Titre","Descriptive statistics","Estadística descriptiva","Statistiques descriptives","Beschreibende Statistiken","Statistica descrittiva","描述统计学","Estatística descritiva","Deskriptivní statistika","विवरणात्मक सांख्यिकी","Beschrijvende statistiek","기술 통계","Beskrivende statistikk","Tanımlayıcı istatistik","Описательная биостатистика","記述統計量",{"$nulls":3},22,23,25,25,22,5,22,23,20,24,5,22,22,26,5,0]
[null,"Number of samples (n)",null,9,"Titre","Number of samples (n)","Número de muestras (n)","Nombre d'échantillons (n)","Anzahl der Stichproben (n)","Numero di campionamenti (n)","样品数目（n）","Número de amostras (n)","Počet vzorků","नमूनों की संख्या (n)","Aantal gegevens (n)","표본의 수 (n)","Antall målinger (n)","Örneklem sayısı (n)","Количество  выборочных совокупностей (n)","サンプル数",{"$nulls":3},21,22,25,26,27,7,22,12,20,19,9,19,19,40,5,0]
[null,"Maximum (max)",null,10,"Titre","Maximum (max)","Máximo (máx.)","Maximum (max)","Maximum (max)","Massimo (max)","最大值（max）","Máximo (Max)","Maximum (max)","महत्तम","Maximum (max)","최대 (max)","Maksimum (maks)","Maksimum (Maks)","Максимум (max)","最大値(max)",{"$nulls":3},13,13,13,13,13,8,12,13,6,13,8,15,15,14,8,0]
[null,"Minimum (min)",null,11,"Titre","Minimum (min)","Mínimo (min.)","Minimum (min)","Minimum (min)","Minimo (min)","最小值（min）","Mínimo (min)","Minimum (min)","न्यूनतम","Minimum (min)","최소 (min)","Minimum (min)","Minimum (Min)","Минимум (min)","最小値(min)",{"$nulls":3},13,13,13,13,12,8,12,13,7,13,8,13,13,13,8,0]
[null,"Range",null,12,"Titre","Range","Rango","Étendue","Spannweite","Intervallo","范围","Faixa","Rozsah","श्रेणी","Bereik","범위","Variasjonsbredde","Örneklem dağılımı ","Диапазон колебаний","範囲",{"$nulls":3},5,5,7,10,10,2,5,6,6,6,2,16,18,18,2,0]
[null,"Percent above OEL",null,13,"Titre","Percent above OEL","Porcentaje por encima del LEO","Pourcentage au-dessus de la VLE","Prozentsatz über dem MAK-Wert","Percentuale superiore al valore di soglia ","超过OEL的百分数","Porcentagem acima LEO","Procenta nad EL","ओईएल से % अधिक","Percentage boven GBB","직업 노출 기준 이상의 퍼센트","Prosent over YGV","OEL üstü yüzde","Процент превышающий ЛПО","ばく露限界値を超えている割合",{"$nulls":3},17,29,31,29,42,9,21,15,14,20,16,16,14,23,14,0]
[null,"Mean ",null,14,"Titre","Mean ","Media","Moyenne","Mittelwert","Media ","均数","Média","Průměr","मध्य","Gemiddelde","평균","Gjennomsnitt","Ortalama","Средняя величина","平均値",{"$nulls":3},5,5,7,10,6,2,5,6,4,10,2,12,8,16,3,0]
[null,"Median",null,15,"Titre","Median","Mediana","Médiane","Median","Mediana","中位数","Mediana","Median","मध्यस्थ","Mediaan","중앙값","Median","Ortanca ","Медианa","中央値",{"$nulls":3},6,7,7,6,7,3,7,6,7,7,3,6,8,7,3,0]
[null,"Standard deviation (s)",null,16,"Titre","Standard deviation (s)","Desviación Estándar (s)","Écart-type (s)","Standardabweichung (s)","Deviazione standard","标准差（s）","Desvio padrão (s)","Standardní odchylka","मानक विचलन","Standaardafwijking (s)","표준 편차 (s)","Standardavvik (s)","Standart sapması","Стандартно(ы)е отклонение(я)","標準偏差(s)",{"$nulls":3},22,23,14,22,19,6,17,19,10,22,9,17,16,28,7,0]
[null,"Mean of logtransformed data (LN)",null,17,"Titre","Mean of logtransformed data (LN)","Media de datos log-transformados (LN)","Moyenne des données log-transformées (LN)","Mittelwert von log-transformierten Daten (LN)","Media dei dati log-trasformati","对数转换后（LN）的均数","Média de dados Log-transformados (LN)","Průměr logaritmicky-transformovaných dat (LN)","लोग रूपांतरित डाटा का मध्य","Gemiddelde van loggetransformeerde gegevens (LN)","로그변환된 자료의 평균값 (LN)","Gjennomsnitt av logtransformertedata (LN)","Logaritması alınmıs ortalama veri","Логарифм средней величины (LN)","対数変換値の平均値",{"$nulls":3},32,37,41,45,30,12,37,45,26,48,18,41,33,30,9,0]
[null,"Standard deviation of log-transformed data (LN)",null,18,"Titre","Standard deviation of log-transformed data (LN)","Desviación Estándar de datos log-transformados (LN)","Écart-type des données log-transformées (LN)","Standardabweichung von log-transformierten Daten (LN)","Deviazione standard dei dati log-trasformati","对数转换后（LN）的标准差","Desvio padrão de dados log-transformados (LN)","Standardní odchylka logaritmicky-transformovaných dat (LN)","लोग रूपांतरित डाटा का मानक विचलन","Standaardafwijking van loggetransformeerde gegevens (LN)","로그변환된 자료의 표준 편차 (LN)","Standardavvik av logtransformertedata (LN)","Logaritması alınmıs standart sapmalı veri","Логарифм данных  стандартного отклонения, ( LN)","対数変換値の標準偏差",{"$nulls":3},47,51,44,53,44,13,45,58,32,56,20,42,41,47,10,0]
[null,"Geometric mean",null,19,"Titre","Geometric mean","Media geométrica","Moyenne géométrique","Geometrisches Mittel","Media geometrica","几何均数","Média geométrica","Geometrický průměr","भौमितिक मध्यमान","Geometrisch gemiddelde","기하평균","Geometrisk gjennomsnitt","Geometrik ortalama","Средняя геометрическая величина","幾何平均値",{"$nulls":3},14,16,19,20,16,4,16,18,15,22,4,23,18,31,5,0]
[null,"Geometric standard deviation",null,20,"Titre","Geometric standard deviation","Desviación estándar geométrica DEG","Écart-type géométrique (GSD)","Geometrische Standardabweichung","Deviazione standard geometrica","几何标准差","Desvio padrão geométrico ","Standardní geometrická odchylka","भौमितिक मानक विचलन","Geometrische standaardafwijking","기하 표준 편차","Geometrisk standardavvik","Geometrik standart sapma","Геометрическое стандартное отклонение","幾何標準偏差",{"$nulls":3},28,34,28,31,30,5,25,31,18,31,8,24,24,37,6,0]
[null,"Test for distribution fit",null,21,"Titre","Test for distribution fit","Prueba de ajuste de una distribución ","Test d'ajustement a une distribution","Anpassungstest für eine Verteilung","Test di conformità ","分布拟合度检验","Teste de ajuste de uma distribuição","Test rozdělení dat","वितरण उचितता का परीक्षण","Toets voor de vorm van de verdeling","분포 적합도 검정","Test av fordeling","Uygunluk dağılımı analizi","Тест на соответствие к распределению","分布の適合度の検定",{"$nulls":3},25,37,36,34,19,7,35,18,23,35,9,17,25,36,9,0]
[null,"W-test of log-transformed data",null,22,"Titre","W-test of log-transformed data","Prueba W de datos log-transformados","Test W sur les données log-transformées","W-Test für die log-transformierten Daten","Test-W sui dati log-trasformati","对数转换数据的W检验","Teste-W de dados log-transformados","W-test logaritmicky-transformovaných dat","लोग रूपांतरित डाटा का W-परीक्षण","W-test van loggetransformeerde gegevens","로그변환된자료의 W-검정","W-test for log-transformerte data","Logaritması alınmış W-analizi","Тест W  данных преобразованных в логарифм","対数変換値のW検定",{"$nulls":3},30,35,39,40,31,10,34,40,31,39,13,33,29,41,9,0]
[null,"Lognormal (α = 0.05) ?",null,23,"Titre","Lognormal (α = 0.05) ?","Log-Normal (α = 0.05)?","Lognormal (α = 0,05) ?","Lognormal (a = 0.05) ?","Log-normale (α = 0,05) ?","对数正态分布（α = 0.05）？","Lognormal (α = 0,05)?","Logaritmicko-normální (α = 0,05) ","लोग नोर्मल (α = 0.05) ?","Lognormaal (α = 0.05) ?","로그정규분포 (유의수준, α=0.05)?","Lognormal (α = 0,05) ?","Lognormal (α = 0.05) ?","Данные логнормальные  (α = 0.05) ?","対数正規分布か?(α=0.05)",{"$nulls":3},22,22,22,22,24,17,21,33,23,23,22,22,22,34,16,0]
[null,"W-test of data",null,24,"Titre","W-test of data","Prueba o Test-W de datos ","Test W sur les données","W-Test für die Daten","Test-W sui dati ","数据的W检验","Teste-W de dados","W-test ","डाटा का W-परीक्षण","W-test van de gegevens","자료의 W-검정","W-test","Veri W-analizi","Данные W- теста","データ値のW検定",{"$nulls":3},14,25,22,20,16,6,16,7,17,22,8,6,14,15,8,0]
[null,"Normal (α = 0.05) ?",null,25,"Titre","Normal (α = 0.05) ?","Normal (α = 0.05) ?","Normal (α = 0,05) ?","Normal (a = 0.05) ?","Normale (α = 0,05) ?","正态分布（α = 0.05）？","Normal (α = 0,05)?","Normální  (α = 0.05) ","नोर्मल (α = 0.05) ?","Normaal (α = 0.05) ?","정규분포 (유의수준, α=0.05)?","Normal (α = 0,05) ?","Normal (α = 0.05) ?","Нормальные данные (α = 0.05) ?","正規分布か?(α=0.05)",{"$nulls":3},19,19,19,19,20,15,18,21,19,20,20,19,19,30,14,0]
[null,"Lognormal parametric statistics",null,26,"Titre","Lognormal parametric statistics","Estadísticas paramétricas para distribuciones Log-normales","Paramètres statistiques pour la distribution lognormale","Parameterstatistiken für die logarithmische Normalverteilung","Parametri statistici per la distribuzione lognormale","对数正态分布参数统计","Estatísticas Paramétricas Lognormais","Logaritmicko-normální statistické parametry","लोग नोर्मल प्राचलिक सांख्यिकी","Parameterstatistiek van de lognormale verdeling","로그정규 모수적 통계량","Lognormal parametrisk statistikk","Lognormal parametrik istatistik","Логнормальная параметрическая статистика","対数正規パラメトリック統計量",{"$nulls":3},31,58,55,60,52,10,36,43,29,47,12,32,31,40,14,0]
[null,"Estimated Arithmetic Mean - AM est.",null,27,"Titre","Estimated Arithmetic Mean - AM est.","Media aritmética estimada (MA  est.)","Moyenne arithmétique estimée (MA est.)","Geschätzter arithmetischer Mittelwert","Stimatore della media aritmetica (MA est.)","估计的算术均数-AM est.","Média Aritmética Estimada - MA est.","Odhadovaný aritmetický průměr - AP odh.","अनुमानित गाणितिक मध्यमान - एएम अनु.","Geschat Rekenkundig Gemiddelde - RG ges.","추정 산술 평균","Estimert aritmetisk gjennomsnitt - AG est.","Tahmini aritmetik ortalama","Расчитанное среднее арифметическое -  Среднее арифметическое","算術平均値の推定値",{"$nulls":3},35,36,38,37,42,15,35,39,35,40,8,42,26,60,9,0]
[null,"LCL1,95% - Land's \"Exact\"",null,28,"Titre","LCL1,95% - Land's \"Exact\"","LCI1, 95% - Land's \"Exacto\"","LCinf. 1,95% - méthode \"Exacte\" de Land","UKG1,95% - Lands \"genaue\" Methode","LCinf. 1,95% - Metodo \"esatto\"  di Land","LCL1，95% - Land's \"确切\"法","LCI 1,95% - Land's \"Exato\"","LCL1,95% - Landova přesná metoda","एलसीएल1, 95% - भूमि का 'वास्तविक'","OBL1,95% - Land's \"Exact\"","신뢰하한1, 95% - Land's \"정확성\"","NKG 1,95% - Land's \"Exact\"","LCL %1.95 - Land's ''Kesin'' sonuç","НДП 1,95% - Точное Лэнда","LCL1,95% - Landの正確法",{"$nulls":3},25,27,39,33,39,23,26,32,33,25,25,26,34,24,19,0]
[null,{"$f":"Translation(D36,trad,Language)","v":"UCL1,95% - Land's \"Exact\""},null,29,"Titre","UCL1,95% - Land's \"Exact\"","LCS1, 95% - Land's \"Exacto\"","LCsup. 1,95% - Méthode \"Exacte\" de Land","OKG1,95% - Lands \"genaue\" Methode","LCsup. 1,95% - Metodo \"esatto\"  di Land","UCL1，95% - Land's “确切”法","LCS 1,95% - Land's \"Exato\"","UCL1,95% - Landova přesná metoda","युसीएल1, 95% - भूमि का 'वास्तविक'","BBL1,95% - Land's \"Exact\"","신뢰상한1, 95% - Land's \"정확성\"","ØKG 1,95% - Land's \"Exact\"","UCL %1.95 -  Land's ''Kesin'' sonuç","ВДП1,95% - Точное Лэнда","UCL1,95% - Landの正確法",{"$nulls":3},25,27,39,33,39,23,26,32,33,25,25,26,35,23,19,0]
[null,"95th Percentile",null,30,"Titre","95th Percentile","Percentil 95","95ieme Percentile","95. Perzentile","95simo Percentile","第95百分位数","Percentil 95","95. percentil","95चां प्रतिशत","95ste Percentiel","95번째 백분위 수","95 persentilen","%95'lik dilim ","95й Процентиль","95パーセンタイル",{"$nulls":3},15,12,17,14,17,7,12,13,13,16,10,14,14,14,9,0]
[null,"UTL95%,95%",null,31,"Titre","UTL95%,95%","LTS 95%, 95%","LTsup. 95%,95%","OTG95%,95%","LTsup. 95%,95%","UTL95%,95%","LTS 95%,95%","UTL95%, 95%","युटीएल95%, 95(((%)))","BTL95%,95%","95% 상위허용한계, 95%","ØTG95%,95%","UTL%95,%95","Верхний Предел 95%,95%","UTL95%,95%",{"$nulls":3},10,12,14,10,14,10,11,11,20,10,15,10,10,22,10,0]
[null,"Percent above OEL",null,32,"Titre","Percent above OEL","Fracción excedente del LEO","Fraction de dépassement la VLE","Prozentsatz über dem MAK-Wert","Percentuale superiore al valore di soglia","超过OEL的百分数","Porcentagem acima do LEO","Procenta nad EL","ओईएल् से  % अधिक","Percentage boven GBB","직업 노출 기준 이상 퍼센트","Prosent over YGV","OEL üzeri yüzde","Процент превышающий ЛПО","ばく露限界値を超える割合",{"$nulls":3},17,26,30,29,41,9,24,15,16,20,15,16,15,23,12,0]
[null,"LCL1,95% %>OEL",null,33,"Titre","LCL1,95% %>OEL","LCI1, 95%, %>OEL","LCinf. 1,95% %>VLE","UKG1,95% %>MAK","LCinf. 1,95% %>TLV","LCL1,95% %>OEL","LCI 1,95% %>LEO","LCL1, 95% %>EL","एलसीएल1, 95% > ओइएल","OBL1,95% %>GBB","신뢰하한1, 95% %> 직업 노출 기준","NKG1,95% %>YGV","LCL %1.95 %>OEL","НДП  1,95%  % > ЛПО","LCL1,95% %>ばく露限界値",{"$nulls":3},14,16,18,14,18,14,15,14,19,14,22,14,15,19,17,0]
[null,"UCL1,95% %>OEL",null,34,"Titre","UCL1,95% %>OEL","LCS1, 95%, %>OEL","LCsup. 1,95% %>VLE","OKG1,95% %>MAK","LCsup. 1,95% %>TLV","UCL1,95% %>OEL","LCS 1,95% %>LEO","UCL1, 95% %>EL","युसीएल1, 95% > ओइएल","BBL1,95% %>GBB","신뢰상한1, 95% %> 직업 노출 기준","ØKG1,95% %>YGV","UCL %1.95 %>OEL","ВДП  1,95%  % >ЛПО","UCL1,95% %>ばく露限界値",{"$nulls":3},14,16,18,14,18,14,15,14,19,14,22,14,15,18,17,0]
[null,"Normal parametric statistics",null,35,"Titre","Normal parametric statistics","Estadísticas paramétricas para distribuciones normales","Paramètres statistiques pour la distribution normale","Parameterstatistiken für die Normalverteilung","Parametri statistici per la distribuzione lognormale","正态分布参数检验","Estatísticas Paramétricas Normais","Statistické parametry pro normální rozdělení","सामान्य प्राचलिक सांख्यिकी","Parameterstatistiek van de normale verdeling","정규 모수적 통계","Normal parametrisk statistikk","Normal parametrik istatistik","Нормальная параметрическая статистика","正規パラメトリック統計量",{"$nulls":3},28,54,52,45,52,8,33,44,26,44,9,29,28,37,12,0]
[null,"Mean",null,36,"Titre","Mean","Media","Moyenne","Mittelwert","Media","均数","Média","Průměr","मध्य","Gemiddelde","평균","Gjennomsnitt","Ortalama","Средняя величина","平均値",{"$nulls":3},4,5,7,10,5,2,5,6,4,10,2,12,8,16,3,0]
[null,"LCL1,95% - t statistics",null,37,"Titre","LCL1,95% - t statistics","LCI1, 95% - estadística-t ","LCinf. 1,95% - t statistiques","UKG1,95% - t-Statistiken","LCinf. 1,95% - test t","LCL1,95% - t检验","LCI 1,95% - statísticas t","LCL1,95% - t statistiky","एलसीएल1, 95% - t सांख्यिकी","OBL1,95% - t statistiek","신뢰하한1, 95% -t 통계","NKG1,95% - t statistikk","LCL %1.95 - t istatistiği","НДП 1,95% - статистический t тест ","LCL1,95% - t分布",{"$nulls":3},23,26,29,24,21,14,25,23,26,23,16,23,25,34,14,0]
[null,"UCL1,95% - t statistics",null,38,"Titre","UCL1,95% - t statistics","LCS1, 95% - estadística-t","LCinf. 1,95% - t statistiques","OKG1,95% - t-Statistiken","LCsup. 1,95% - test t","UCL1,95% - t检验","LCS 1,95% - statisticas t","UCL1,95% - t statistiky","युसीएल1, 95% - t सांख्यिकी","BBL1,95% - t statistiek","신뢰상한1, 95% -t 통계","ØKG1,95% - t statistikk","UCL %1.95 - t istatistiği","ВДП 1,95% - статистический t тест ","UCL1,95% - t分布",{"$nulls":3},23,25,29,24,21,14,25,23,26,23,16,23,25,34,14,0]
[null,"95th Percentile - Z",null,39,"Titre","95th Percentile - Z","Percentil 95 - Z","95ieme Percentile - Z","95. Perzentile - Z","95simo Percentile - Z","第95百分位数 - Z","Percentil 95 - Z","95. percentil - Z","95चां प्रतिशत - Z","95ste Percentiel - Z","95번째 백분위 수 -Z","95 persentilen – Z","%95'lik dilim - Z","95й Процентиль - Z","95パーセンタイル",{"$nulls":3},19,16,21,18,21,11,16,17,17,20,13,18,17,18,9,0]
[null,"UTL95%,95%",null,40,"Titre","UTL95%,95%","LTS 95%, 95%","LTsup. 95%,95%","OTG95%,95%","LTsup. 95%,95%","UTL95%,95%","LTS95%,95%","UTL95%,95%","युटीएल95%, 95%","BTL95%,95%","95% 상위허용한계, 95%","ØTG95%,95%","UTL%95,%95","Верхний Предел  95%, 95%","UTL95%,95%",{"$nulls":3},10,12,14,10,14,10,10,10,14,10,15,10,10,24,10,0]
[null,"UTL",null,40.1,"Graph","UTL","LTS","LTsup.","OTG","LTsup.","UTL","LTS","UTL","युटीएल","BTL","상위허용한계","ØTG","UTL","Верхний Предел","UTL",{"$nulls":3},3,3,6,3,6,3,3,3,6,3,6,3,3,14,3,0]
[null,"Percent above OEL",null,41,"Titre","Percent above OEL","Porcentaje mayor que LEO","Pourcentage au-dessus de la VLE","Prozentsatz über dem MAK-Wert","Percentuale superiore al valore di soglia ","超过OEL的百分数","Porcentagem acima do LEO","Procenta nad EL","ओईएल से % अधिक","Percentage boven GBB","직업 노출 기준 이상의 퍼센트","Prosent over YGV","OEL üzeri yüzde","Процент, превышающий ЛПО","ばく露限界値を超える割合",{"$nulls":3},17,24,31,29,42,9,24,15,14,20,16,16,15,24,12,0]
[null,"Sequential Data Plot",null,42,"Graph","Sequential Data Plot","Gráfico secuencial de datos","Graphique séquentiel des données","Sequentielle Datengraphik","Grafico sequenziale","连续资料图","Gráfico de dados sequenciais","Sekvenční zobrazení dat","क्रमिक डाटा प्लोट","Sequentiële Gegevens Diagram","연속자료도표","Tidsserieplott","Ardaşık veri dizisi","Данные в последовательном порядке","データ順のプロット",{"$nulls":3},20,27,32,25,19,5,28,23,17,28,6,14,19,33,9,0]
[null,"Logprobability Plot and Least-Squares Best-Fit Line",null,43,"Graph","Logprobability Plot and Least-Squares Best-Fit Line","Gráfico de Log-probabilidades y regresión lineal","Graphique log-probabilité et droite des moindres carrés","Logarithmischer Wahrscheinlichkeitsplot und beste Anpassungskurve der kleinsten Quadrate","Curva di log-probabilità e retta dei minimi quadrati","对数概率分布散点图和最小方差线性拟合图","Gráfico de Logprobabilidade e Regressão Linear","Logaritmická distribuce pravděpodobnosti s regresní křivkou","लोग संभाव्यता प्लोट एवं न्यूनतम वर्ग श्रेष्ठ-उचित रेखा","Lognormaal Waarschijnlijkheidsdiagram en best passende rechte (kleinste kwadraten)","로그확률산포도와 최소제곱최적선","Log sannsynlighetsplott med Minste kvadrats linjetilpasning","Log-olasılık dizisi ve En Küçük Kareler Uygunluk Çizgisi","Графики Лог. вероятности и Выравнения по методу наименьших квадратов","対数確率プロットと最小二乗最適近似線",{"$nulls":3},51,48,55,88,52,19,46,59,54,82,16,59,56,68,18,0]
[null,"Linear Probability Plot and Least-Squares Best-Fit Line",null,44,"Graph","Linear Probability Plot and Least-Squares Best-Fit Line","Gráfico de Probabilidad y regresión lineal  ","Graphique probabilité et droite des moindres carrés","Linearer Wahrscheinlichkeitsplot und beste Anpassungskurve der kleinsten Quadrate","Curva di probabilità e retta dei minimi quadrati","线性概率分布散点图和最小方差线性拟合图","Gráfico de Probabilidade e Regressaõ Linear","Lineární distribuce pravděpodobnosti s regresní křivkou","रैखिक संभाव्यता प्लोट एवं न्यूनतम वर्ग श्रेष्ठ-उचित रेखा","Lineair Waarschijnlijkheidsdiagam en best passende rechte (kleinste kwadraten)","대수확률산포도와 최소제곱최적선","Linear sannsynlighetsplott med Minste kvadrats linjetilpasning","Doğrusal Olasılık ve  En Küçük Kareler Uygunluk Çizgisi","Графики Линейной вероятности и  Выравнения по методу наименьших квадратов","線形確率プロットと最小二乗最適近似線",{"$nulls":3},55,44,51,81,48,19,43,55,56,78,16,62,55,73,18,0]
[null,"Idealized Lognormal Distribution",null,45,"Graph","Idealized Lognormal Distribution","Distribución Log-normal Ideal","Distribution log-normale idéale","Ideale logarithmische Normalverteilung","Distribuzione log-normale ideale","理想的对数正态分布","Distribuição Lognormal Idealizada","Ideální logaritmicko-normální distribuce","आदर्श लोग नोर्मल वितरण","Geïdealiseerde lognormale verdeling","이상형 로그정규 분포","Normalisert Lognormalfordeling","İdeal durumdaki Lognormal Dağılım","Стандартное логнормальное распределение","理想対数正規分布",{"$nulls":3},32,29,31,38,32,9,33,40,22,35,11,30,33,39,8,0]
[null,"Occupational Exposure Limit.",null,45.5,"comm.\nConcept","Occupational Exposure Limit.","Valor Límite de Exposición Ocupacional (LEO)","Valeur limite d'exposition professionnelle","Maximale Arbeitsplatz-Konzentration","Valori limite d'esposizione professionale","职业接触限值","Limite de exposição ocupacional","Pracovní expoziční limit","व्यावसायिक  एक्सपोजर सीमा","Grenswaarde voor Beroepsmatige Blootstelling","직업 노출 기준","Yrkesmessig tiltaks- eller grenseverdi (YGV)","Mesleki Maruziyet Limiti (OEL)","Лимит профессионального облучения","ばく露限界値",{"$nulls":3},28,44,42,35,41,6,31,24,25,44,8,44,30,33,6,0]
[null,"Reference value ( may be a TLV® , PEL, REL …)",null,45.7,"comm.\nConcept","Reference value ( may be a TLV® , PEL, REL …)","Valor de referencia (puede ser TLV® , PEL, REL …)","Valeur de référence (peut être TLV® , PEL, REL …)","Referenzwerte (z.B. TLV® , PEL, REL …)","Valore di referenza (per esempio TLV®, PEL, REL …)","参考值 （可以是一个TLV® , PEL, REL数值等）","Valor de referência (pode ser um TLV®, PEL, REL…)","Referenční hodnota (může být TLV® , PEL, NPK  …)","संदर्भ मूल्य ( TLV® , PEL, REL )","Referentiewaarde (kan een TLV®, PEL, REL,… zijn)","기준값 [노출기준 (TLV), 허용노출기준 (PEL), 권장노출기준 (REL)]","Referanseverdi (kan være YGV, TLV®, PEL, REL, WEEL, WEL …)","Referans değeri (TLV® , PEL, REL … ve bunun gibi)","Справочная величина(ПДК, и т.д.)","参照値（TLV@, PEL, REL…など） ",{"$nulls":3},45,49,49,38,50,29,49,48,32,48,44,58,49,32,23,0]
[null,"max n = 200",null,45.8,"comm.\nConcept","max n = 200","max n = 200","max n = 200","max n = 200","max n = 200","最大数目 n = 200","max n = 200","max n = 200","महत्तम N = 200","max n = 200","최대 시료수=200","maks n = 200","Maksimum n = 200","max n = 200","最大 n=200",{"$nulls":3},11,11,11,11,11,12,11,11,14,11,10,12,16,11,8,0]
[null,"The difference between the largest and the smallest values in a measurement data set.",null,46,"comm.\nConcept","The difference between the largest and the smallest values in a measurement data set.","La diferencia entre el mayor y el menor valor en un conjunto de datos.","La différence entre la valeur la plus élevée et la valeur la plus faible dans un ensemble de données.","Der Unterschied zwischen dem höchsten Wert und dem kleinsten Wert in einer Datengruppe von Messwerten.","La differenza tra il valore piu' alto e piu' basso per un insieme di dati.","在一个测量的数据集中的最大值和最小值之差","A diferença entre o maior e o menor valor em um conjunto de dados.","Rozdíl mezi nejvyššími a nejnižšími hodnotami v měřeném souboru dat.","मापन डाटा सेट में रहे महत्तम एवं न्यूनतम मूल्यों के बीच का अंतर","Het verschil tussen de grootste en kleinste waarde in een set meetgegevens.","측정 데이터 집합내에서 최소값과 최대값의 차이 ","Forskjellen mellom den største og minste verdier i et sett av måledata.","Herhangi bir ölçüm veri seti üzerindeki en büyük ve en küçük değerler arasındaki fark","Разница между  наибольшой и наименьшей величиной в измеренной совокупности данных.","1群の測定値中の最大値と最小値の差",{"$nulls":3},85,70,101,102,74,20,66,68,63,75,26,71,85,82,17,0]
[null,"The arithmetic average of the set of data.",null,47,"comm.\nConcept","The arithmetic average of the set of data.","El promedio aritmético de un conjunto de datos.","La moyenne arithmétique des données.","Der arithmetische Mittelwert der Datengruppe.","La media aritmetica dei dati.","该数据集的算术均数","A média aritmética do conjunto de dados.","Aritmetický průměr souboru dat.","डाटा सेट का गाणितिक औसत","Het rekenkundig gemiddelde van de gegevens.","데이터 집합의 산술 평균","Det aritmetiske gjennomsnitt av et datasett.","Veri dizisinin aritmetik ortalaması"," Среднее арифметическое  набора данных","1群の測定値の算術平均値．",{"$nulls":3},42,47,36,45,29,9,40,31,23,43,13,44,35,38,13,0]
[null,"The exposure measurement that divides the set of measurements into two equal parts, whith half less half greater than this value.",null,48,"comm.\nConcept","The exposure measurement that divides the set of measurements into two equal parts, whith half less half greater than this value.","Medida de exposición que divide un conjunto de mediciones en dos partes iguales, siendo la mitad menor y la mitad mayor de dicho valor.","La valeur qui partage l'ensemble des données en deux parties égales, une moitié étant inférieure et l'autre moitié étant supérieure à cette valeur.","Der Expositionsmesswert, der die Messwertegruppe in zwei gleiche Gruppen einteilt, eine Hälfte mit kleineren Werte und eine Hälfte mit grösseren Werte als dieser Expositionsmesswert.","Il valore che divide l'insieme ordinato dei valori in due parti uguali, una metà inferiore e l'altra superiore a questo valore.","该接触测量值将所有的测量数据分成两个相等的部分，一半数据小于该数值，而另一半大于该数值","O valor de exposição que divide o conjunto de medições em duas partes iguais, com metade dos valores abaixo e a outra metade acima deste valor.","Tato hladina expozice dělí soubor měření na dvě stejné části, polovina s vyšší a polovina s nižší expozicí než je tato hodnota.","एक्सपोजर मापन, जो मापन के सेट को दो समान हिस्सों में विभाजित करता है, जो इस मूल्य से आधा कम और आधा ज्यादा होता है.","De blootstellingsmeting die de set gegevens in twee gelijke delen verdeelt, waarbij de ene helft groter en de andere helft kleiner is dan deze waarde.","노출 측정을 동등하게 두 부분으로 (반은 노출측정값보다 작고, 반은 노출측정값보다 큰) 분할한 측정 집합","Eksponeringsmåling som skiller målingene i to like deler, med halvdel mindre og halv større enn denne verdien.","Ölçüm setini iki eşit parçaya bölen (yarıdan az, yarıdan çok) maruziyet ölçümü ","Среднее арифметическое профессионального облучения, разделяющее набор данных на две равные части : одна половина с данными меньше и другая половина с данными больше, чем значение СА профессионального облучения.","ある測定値で，全測定値群をその値より小さいものと大きいのものの等しい2群に分けるもの．",{"$nulls":3},129,135,147,182,127,43,143,127,114,150,58,110,79,210,43,0]
[null,"The positive square root of the variance of a distribution; the parameter measuring spread of values about the mean.",null,49,"comm.\nConcept","The positive square root of the variance of a distribution; the parameter measuring spread of values about the mean.","La raíz cuadrada positiva de la varianza de una distribución; el parámetro que mide la dispersión de valores desde la media.","La racine carrée de la variance d'une distribution; ce paramètre mesure la dispersion des valeurs autour de la moyenne.","Die positive Quadratwurzel einer Varianzverteilung; dieser Parameter misst die Streuung der Werte um den Mittelwert.","La radice quadrata della varianza di una distribuzione: questo parametro misura la dispersione dei valori intorno alla media","某个分布的方差的正平方根；该参数体现了均数的分布情况","A raiz quadrada positiva da variância de uma distribuição; o parâmetro que mede a dispersão de valores em torno da média.","Kladná druhá odmocnina rozptylu; parametr měřící rozptyl hodnot kolem průměru.   ","वितरण के विचलन का धन स्क्वेयर रूट; मध्य संबंधित मूल्यों के वितरण का मापन करने वाले प्राचल / पैरामीटर","De vierkantswordel van de variantie van een verdeling; een parameter die de spreiding van waarden rondom het gemiddelde beschrijft.","분포 분산의 양의 제곱근; 평균값의 확산을 측정하는 매개변수","Den positive kvadratroten av variansen til et datasett; dette er et mål på spredningen av verdiene rundt gjennomsnittet.","Dağılımın varyans değerinin pozitif karekökü; değerlerin ortalamadan dağılımını ölçen parametre","Положительный квадратный корень изменения распространения. Этот параметр измеряет распределение замерений  приболиженных к средней величине.","分布の分散の平方根．平均値の周囲へのデータの広がりを示す変数．",{"$nulls":3},116,124,119,116,124,26,121,81,100,131,33,120,95,140,31,0]
[null,"The exponential of the arithmetic mean of the natural logarithms of the data.The geometric mean is the theoretical median of lognormaly distributed data.",null,50,"comm.\nConcept","The exponential of the arithmetic mean of the natural logarithms of the data.The geometric mean is the theoretical median of lognormaly distributed data.","Exponencial de la media aritmética de los logaritmos naturadesde los datos.La media geométrica es la mediana teórica de una distribución log-normal.","L'exponentiel de la moyenne arithmétique des logarithmes népériens des valeurs. La moyenne géométrique est la médiane théorique d'une distribution log-normale. ","Die Exponential des arithmetischen Mittelwertes der natürlichen Logarithmen der Daten. Das geometrische Mittel ist der theoretische Median lognormalen verteilten Daten.","L'esponenziale della media aritmetica del logaritmo neperiano dei valori. La media geometrica é la mediana teorica di una distribuzione log-normale.","数据的自然对数的算术均数的指数。理论上对数正态分布数据的中位数是它们的几何均数。","O exponencial da média aritmética dos logaritmos naturais dos dados. A média geométrica é a mediana teórica de uma distribuição lognormal.","Exponenciální aritmetický průměr přirozených logaritmů dat. Geometrický průměr je teoretická středová hodnota logaritmicko-normálně rozdělených dat.","डाटा के नेचरल लोगेरिधम के गाणितिक मध्य का एक्स्पोनेन्शियल. भौमितिक मध्य, लोगनोर्मली वितरित डाटा का सैध्दांतिक मध्यस्थ है.","De exponent van het rekenkundig gemiddelde van de natuurlijke logaritmes van de gegevens. Het geometrisch gemiddelde is de theoretische mediaan van lognormaal verdeelde data.","데이터의 자연로그된 산술평균 지수. 기하평균은 로그정규 분포된 데이터의 이론적 평균입니다.","Den eksponentielle av det aritmetiske gjennomsnittet av de naturlige logaritmer av data. Det geometriske gjennomsnitt er den teoretiske median i en fordeling av lognormaledata.","Verinin doğal logaritmasının aritmetik ortalamasının üstel değeri (eksponansiyel değeri). Lognormal dağılım gösteren verinin teorik ortanca değeri geometirk ortalamadır.","Показательная функция натурального логарифма среднего  арифметического данных . Геометрическое среднее - это теоретическая медиана логнормально распределенных данных.","測定値の自然対数の算術平均値に指数関数（e）を適用した値（注：ここで、測定値の常用対数の算術平均値の場合は指数関数（10）を適用した値）．幾何平均値は理論上、対数正規分布しているデータの中央値に相当する．",{"$nulls":3},153,148,160,168,148,40,138,148,121,174,50,176,169,166,102,0]
[null,"The exponential of the standard deviation of the natural logarithms of the data.\nRelation between GSD and Action Level : to ensure a high probability (95%) that no more than 5% of unmeasured exposures exceed the OEL, the Action Level, must be lowered as the GSD increases, as follows: day-to-day variability, GSD ≤ 1.3, OEL = 0.5 TLV; GSD = 1.5, OEL = 0.25 TLV; GSD = 2.0, OEL = 0.1 TLV; GSD ≥ 3.0, Process out of control or group poorly defined. (Leidel, 1976)",null,51,"comm.\nConcept","The exponential of the standard deviation of the natural logarithms of the data.\nRelation between GSD and Action Level : to ensure a high probability (95%) that no more than 5% of unmeasured exposures exceed the OEL, the Action Level, must be lowered as the GSD increases, as follows: day-to-day variability, GSD ≤ 1.3, OEL = 0.5 TLV; GSD = 1.5, OEL = 0.25 TLV; GSD = 2.0, OEL = 0.1 TLV; GSD ≥ 3.0, Process out of control or group poorly defined. (Leidel, 1976)","El exponencial de la desviación estándar de los logaritmos naturales de los datos. Relación entre DEG y el nivel de acción: El nivel de acción debe bajar a mdeida que aumenta la DEG para asegurar una alta porbabilidad (95%) que no más que 5% de las exposiciones no medidas excedan el LEO, de la siguiente manera: Variabilidad día a día, DEG ≤ 1.3, L EO= 0.5 TLV; DEG = 1.5, LEO = 0.25 TLV; DEG = 2.0, LEO = 0.1 TLV; DEG ≥ 3.0, Proceso fuera de control o pobremente definido. (Leidel, 1976)","L'exponentiel de l'écart-type des logarithmes népériens des données. Relation entre GSD et niveau d'intervention (AL) : pour s'assurer que moins de 5% des expositions ne dépasse la VLE (avec une probabilité d'au moins 95%), le niveau d'intervention doit être réduit à mesure que la variabilité (GSD) augmente : GSD ≤ 1.3, AL = 0.5 VLE; GSD = 1.5, AL = 0.25 VLE; GSD = 2.0, AL = 0.1 VLE; GSD ≥ 3.0, Procédé nom maitrisé ou groupe d'exposition mal défini. (Leidel, 1976)","Die Exponential der Standardabweichung der natürlichen Logarithmen der Daten. Zusammenhang zwischen GSD und dem Wirkungspegel (AL): um eine hohe Wahrscheinlichkeit (95%) zu sichern so dass nicht mehr als 5% der ungemessenen Expositionen die MAK überschreiten, muss der Wirkungspegel senken wenn die GSD steigt, wie folgendes: tagtägliche Variabilität, GSD ≤ 1.3, AL = 0.5 MAK; GSD = 1.5, AL = 0.25 MAK; GSD = 2.0, AL = 0.1 MAK; GSD ≥ 3.0, Prozess ausser Kontrolle oder Expositionsgruppe schlecht bestimmt. (Leidel, 1976)","L'esponenziale della deviazione standard del logaritmo neperiano dei dati. Relazione tra GSD e Action Level (limite d'accettazione): per assicurarsi che non piu' del 5% dei casi d'esposizione non misurati superi il valore di soglia (TLV) (con una probabilità di almeno 95%), l'Action Level deve essere ridotto per ottenere un aumento della GSD: GSD ≤ 1.3, AL = 0.5 TLV; GSD = 1.5, AL = 0.25 TLV; GSD = 2.0, AL = 0.1 OEL ?; GSD≥ 3.0, Processo non controllabile o gruppo d'esposizione mal definito. (Leidel, 1976)","数据的自然对数的标准差的指数。GSD和控制水平之间的关系：确保有高的概率（95%）让不超过5%的未测量的接触值超过OEL，控制水平必须随着GSD的增加，根据下列情况降低：日间变异度，GSD≤ 1.3, OEL = 0.5 TLV; GSD = 1.5, OEL = 0.25 TLV; GSD = 2.0, OEL = 0.1 TLV; GSD ≥ 3.0。整个过程失去控制或者对组别定义不好。（Leidel，1976）","O exponencial do desvio-padrão dos logaritmos naturais dos dados. \nRelação entre (Desvio Padrão Geométrico) DPG e Nível de Ação: para garantir uma probabilidade elevada (95%) de que não mais do que 5% das exposições não medidas excedam o LEO, o Nível de Ação deve ser reduzido a medida que o DPG aumenta, como segue: variabilidade dia-a-dia , DPG ≤ 1,3, LEO = 0,5 TLV; DPG = 1,5, LEO = 0,25 TLV; DPG = 2,0, LEO = 0,1 TLV; DPG ≥ 3,0, Processo fora de controle ou grupo pobremente definido. (Leidel, 1976)","Přirozená exponenciála standardní odchylky přirozených logaritmů dat. Poměr mezi GSD a hladinou působení: zajištění vysoké pravděpodobnosti (95%), že méně než 5% z nenaměřených expozic přesáhne EL,  musí se hladina působení snižovat dle nárůstu GSD, následovně: každodenní variabilita, GSD ≤ 1.3, EL = 0.5 TLV; GSD = 1.5, EL = 0.25 TLV; GSD = 2.0, EL = 0.1 TLV; GSD ≥ 3.0, Proces mimo kontrolu nebo špatně definovaná skupina. (Leidel, 1976)","डाटा के नेचरल लोगेरिधम के मानक विचलन का एक्स्पोनेन्शियल. जीएसडी एवं कार्य स्तर के बीच का संबंध : ऐसी उच्च संभाव्यता (95%) सुनिश्चित करना, जिससे अनापित एक्स्पोजर का 5% ओइएल से अधिक न हो, कार्य स्तर, जीएसडी के बढने के साथ नीचे दर्शितानुसार कम होना चाहिए : दैनिक चलनियता, जीएसडी ≤ 1.3, ओइएल = 0.5 टीएलवी; जीएसडी = 1.5, ओइएल = 0.25 टीएलवी; जीएसडी = 2.0,ओइएल = 0.1 टीएलवी; जीएसडी  ≥ 3.0, प्रक्रिया नियंत्रण से बाहर या समूह घटिया रूप से परिभाषित (लैडेल, 1976)","De exponent van de standaardafwijking van de natuurlijke logaritmes van de gegevens. Relatie tussen de GSA en de Actiewaarde (AW): een hoge waarschijnlijkheid garanderen (95%) dat niet meer dan 5% van ongemeten blootstellingen de GBB overschrijden; de AW moet als volgt verlagen naarmate de GSA stijgt: dag-tot-dag variabiliteit, GSA ≤ 1.3, AW = 0.5 GBB; GSA = 1.5, AW = 0.25 GBB; GSA = 2.0, AW = 0.1 GBB; GSA ≥ 3.0. Proces is niet onder controle of de groep is slecht gedefinieerd. (Leidel, 1976)","데이터의 자연로그의 표준편차 지수. 기하표준편차(GSD)와 감시기준(Action level)의 관계: 직업노출기준을 초과한 비측정 노출의 5%일뿐인 높은 확률 (95%)를 보장하기 위해 감시기준은 GSD가 증가함에따라 다음과 같이 낮아져야합니다: 일일 변이,   GSD ≤ 1.3, OEL = 0.5 TLV; GSD = 1.5, OEL = 0.25 TLV; GSD = 2.0, OEL = 0.1 TLV; GSD ≥ 3.0, 통제불능한 과정 혹은 경계가 뚜렷하지 않은 그룹. (Leidel, 1976)","Den eksponentielle av standardavviket av de naturlige logaritmene til dataene. Forhold mellom GSA og \"Tiltaksnivå\" (TN): å sikre en høy sannsynlighet (95%) for at ikke mer enn 5% av den ikke målte eksponeringen overstiger tiltaks- eller grenseverdien (YGV). \"Tiltaksnivået\" må senkes om GSA øker. Hvis GSA ≤ 1,3, TN = 0,5 YGV; GSA = 1,5, TN = 0,25 YGV; GSA = 2,0, TN = 0,1 YGV; GSA ≥ 3,0, prosessen ute av kontroll eller eksponeringsgruppen dårlig definert. (Leidel, 1976) ","Verinin doğal logaritmasının standart sapmasının üstel değeri (eksponansiyel değeri). \nGSD ve Aksiyon Seviyesi arasındaki ilişki: OEL, Aksiyon Seviyesini aşan ölçülmeyen maruziyetleri, %5'den fazla olmayan yüksek bir olasılık (% 95) sağlamak için belirtildiği gibi GSD arttıkça azaltılmalıdır: günlük değişkenlik, GSD ≤ 1.3, OEL = 0.5 TLV; GSD = 1.5, OEL = 0.25 TLV; GSD = 2.0, OEL = 0.1 TLV; GSD ≥ 3.0, Kontrolsüz veya zayıf grup olarak tanımlayarak kaydedin. (LEIDEL, 1976)","Показательная функция  натурального логарифма  данных стандартного отклонения.\nОтношение между  Геометрическим Стандартным Отклонением (ГСО)и Пороговой Дозой вещества: для обеспечения высокой вероятности (95%) при не более 5% неизмеренных данных воздействий, превышающих ЛПО, Пороговая Доза должена быть уменьшена так как ГСО увеличивается, как показано: суточные изменения, ГСО ≤ 1.3, ЛПО = 0.5 ПДК; ГСО = 1.5, ЛПО = 0.25 ПДК; ГСО = 2.0, ЛПО = 0.1 ПДК; ГСО ≥ 3.0, безконтрольный процесс или группа плохо определена. (Leidel, 1976)                                      ","測定値の自然対数の標準偏差値に指数関数（e）を適用した値（注：ここで、測定値の常用対数の標準偏差値の場合は指数関数（10）を適用した値）．\n幾何標準偏差（GSD）とアクションレベルの関係は次の通りである．なお，ここで言うアクションレベルとは，ばく露限界値（OEL）を超えるばく露の割合が5%以下であることを95%の確率で保障するばく露レベルのことであり，GSDが増すに従いアクションレベルを次のように下げる必要がある．GSD=<1.3の時，AL=0.5OEL．GSD=1.5の時，AL=0.25OEL．GSD=2.0の時，AL=0.1OEL．GSDが3.0以上の時，作業工程の管理不十分または同等ばく露グループの定義が不適切．（Leidel, 1976）",{"$nulls":3},461,489,468,520,511,210,503,440,453,497,279,473,475,569,327,0]
[null,"Goodness-of-fit-test; a formal statistical test that evaluates whether sample data are consistent with a statistical distribution",null,52,"comm.\nConcept","Goodness-of-fit-test; a formal statistical test that evaluates whether sample data are consistent with a statistical distribution","Prueba de \"ajuste\"; es una prueba estadística formal que evalúa si la muestra de datos es consistente con una distribución estadística normal. ","Test d'ajustement; un test statistique qui évalue si les données sont conformes à une distribution statistique","Anpassungstest: ein statistischer Test der prüft, ob die Daten mit einer statistischer Verteilung übereinstimmen.","Test di conformità : un test statistico che valuta se i dati sono conformi a una distribuzione statistica","拟合优度检验；用于检验样品数据是否同统计学上的某种分布相一致。","Teste-de-conformidade-de-ajuste; um teste estatístico formal que avalia se uma amostra de dados é consistente com uma distribuição estatística","Test rozdělení dat; test posuzující zda naměřené hodnoty odpovídají zvolenému statistickému rozdělení.","औचित्य परीक्षण का सहीपन ; एक औपचारिक सांख्यिकीय परीक्षण जो नमूना डाटा सांख्यिकीय वितरण से सुसंगत है या नहीं उसका मूल्यांकन करता है.","Toets voor overeenkomst van de vorm van de verdeling; een formele statistische test die evalueert of steekproefgegevens een bepaalde statistische verdeling volgen.","적합도 검정; 표본 데이터가 통계 분포와 일치 여부를 평가하는 공식적 통계 검정","Goodness-of-fit test; en formell statistisk test som vurderer hvorvidt datasettet er i overensstemmelse med en statistisk fordeling.","Uyuşum testi; örnek verinin istatistiksel dağılım ile tutarlı olup olmadığını değerlendiren formal bir istatistik testidir. ","Критерий согласия тест - это формальный статистический тест, определяющий совместимость полученных данных  выборочной совокупности со статистическим распределением.","適合度の検定．サンプル値が統計分布に一致するかどうかを評価するための数学的な統計的検定",{"$nulls":3},129,143,110,113,105,31,142,102,131,163,44,132,124,164,43,0]
[null,"The Shapiro and Wilk test\n(known usually as the W test)",null,53,"comm.\nConcept","The Shapiro and Wilk test\n(known usually as the W test)","Test de Shapiro y Wilk (conocida como la Prueba o Test W)","Test de Shapiro et Francia (connu sous le nom test W)","Der Shapiro-Wilk-Test (gewöhnlich als W-Test bekannt)","Test di Shapiro e Wilk (piu' noto come W-test)","Shapiro 和Wilk检验（经常被称为W检验）","Teste de Shapiro e Wilk \n(Normalmente conhecido como o teste W)","Shapiro a Wilk test (obecně známý jako W test)","शेपिरो एवं विल्क परीक्षण (सामान्यत: W-परीक्षण के रूप में जाना जाता है)","Test van Shapiro en Wilk (meestal bekend onder de naam W-test)","샤피로-윌크 검정 (일반적으로 W 검정으로 알려짐)","Shapiro og Wilk test (kjent vanligvis som W test).","Shapiro-Wilk testi (W testi olarak da bilinir)","Тест Шапиро и Уилка\n(известный так же как тест W)","Shapiro/Wilk検定．（一般にW検定として知られる）．",{"$nulls":3},55,57,53,53,46,25,63,46,70,62,28,50,46,49,31,0]
[null,"Indicate if the exposure profile can or cannot reasonably be approximated by a log normal distribution",null,54,"comm.\nConcept","Indicate if the exposure profile can or cannot reasonably be approximated by a log normal distribution","Indica si el perfil de exposición puede o no ser razonablemente estimado como una distribución log-normal.","Indique si le profil d'exposition est conforme ou non à une distribution log-normale","Deutet an ob das Expositionsprofil durch eine logarithmische Normalverteilung angenähert werden kann","Indica se il profilo d'esposizione é conforme a una distribuzione log-normale","指明该接触资料能不能合理地服从对数正态分布。","Indica se o perfil de exposição pode ou não razoavelmente ser aproximado a uma distribuição lognormal","Značí, zda expoziční profil může nebo nemůže být proložen logaritmicko-normálním rozdělením.","यह दर्शाता है कि एक्स्पोजर प्रोफाईल लोग नोर्मल वितरण द्वारा उचित रूप से अनुमानित होता है या नहीं.","Geeft aan of het blootstellingsprofiel op een redelijke wijze kan benaderd worden door een lognormale verdeling","노출 개요서가 로그 정규 분포에 의해 합리적으로 근사될수 있는지 없는지 표시하십시오.","Angir om eksponeringsprofilen med rimelighet kan eller ikke kan tilnærmes ved en lognormalfordeling.","Maruziyet durumunun log normal dağılıma yaklaşık olup olmadığını belirtin.","Укажите, может или нет, профиль воздействия  быть приемлемо точен по логнормальныму распределению","ばく露分布が対数正規分布で合理的に近似できるかどうかを示す．",{"$nulls":3},102,106,84,100,77,22,101,92,97,111,47,100,74,97,30,0]
[null,"Indicate if the exposure profile can or cannot\nbe approximated by a normal distribution.",null,55,"comm.\nConcept","Indicate if the exposure profile can or cannot\nbe approximated by a normal distribution.","Indica si el perfil de exposición puede o no ser razonablemente estimado como una distribución normal.","Indique si le profil d'exposition est conforme ou non à une distribution normale","Deutet an ob das Expositionsprofil durch eine Normalverteilung angenähert werden kann","Indica se il profile d'esposizione é conforme a una distribuzione normale","指明该接触资料能不能合理地服从正态分布。","Indica se o perfil de exposição pode ou não ser aproximado a distribuição normal.","Značí, zda expoziční profil může nebo nemůže být proložen normálním rozdělením.","यह दर्शाता है कि एक्स्पोजर प्रोफाईल नोर्मल वितरण द्वारा उचित रूप से अनुमानित होता है या नहीं.","Geeft aan of het blootstellingsprofiel op een redelijke wijze kan benaderd worden door een normale verdeling","노출 개요서가 정규 분포에 의해 합리적으로 근사될수 있는지 없는지 표시하십시오.","Angir om eksponeringsprofilen med rimelighet kan eller ikke kan tilnærmes ved en normalfordeling. ","Maruziyet durumunun normal dağılıma yaklaşık olup olmadığını belirtin.","Укажите, может ли полученный профиль воздействия  быть расчитан по нормальному распределению","ばく露分布が正規分布で合理的に近似できるかどうかを示す．",{"$nulls":3},88,102,80,85,73,20,81,79,93,108,44,98,70,92,28,0]
[null,"If the exposure profile indicates that the monitoring data might not come from a lognormal or normal distribution, consider using non parametric statistic.",null,56,"comm.\nConcept","If the exposure profile indicates that the monitoring data might not come from a lognormal or normal distribution, consider using non parametric statistic.","Si el perfil de exposición indica que los datos del monitoreo no proceden de una distribución log-normal o normal, considere la utilización de pruebas estadísticas no paramétricas. ","Si le profil d'exposition indique que les données d'échantillonnage ne proviennent probablement pas d'une distribution normale ou log-normale, utiliser alors les statistiques non paramétriques.","Wenn das Expositionsprofil andeutet dass die Monitoring-Daten nicht mit einer logarithmischen Normalverteilung oder mit einer Normalverteilung übereinstimmen, dann parameterfreie Statistik anwenden.","Se il profilo d'esposizione indica che i dati di campionamento non provengono probabilmente da una distribuzione normale o log-normale, utilizzare test non parametrici","如果接触资料表明该监测数据不是来自于一个对数正态分布或者正态分布总体，那么考虑使用非参数统计方法。","Se o perfil de exposição indicar que o dado de monitoramento pode não pertencer a uma distribuição normal ou lognormal, considerar o uso de estatística não-paramétrica.","Pokud expoziční profil indikuje, že monitorovací data možná nepochází z log-normální distribuce, zvažte užití neparametrické statistiky.","यदि एक्स्पोजर प्रोफाईल यह दर्शाता है कि अनुश्रवित डाटा लोग नोर्मल या नोर्मल वितरण से नहीं आता है तो गैर प्राचलिक सांख्यिकी का उपयोग करने पर विचार किया जाए.","Als het blootstellingsprofiel aangeeft dat de meetgegevens niet uit een lognormale of normale verdeling zouden komen, overweeg dan om niet-parametrische statistiek te gebruiken.","노출 개요서에서 모니터링 데이터가 로그정규 혹은 정규 분포에서 나오지 않았다면 비모수적통계 사용을 고려하십시오.","Hvis eksponering profilen indikerer at måledata ikke kan komme fra en lognormal- eller normalfordeling, vurdere å bruke ikke parametrisk statistikk.","Eğer maruziyet durumu, görüntülenen verinin lognormal veya normal dağılıma uymayabileceğini gösteriyorsa, parametrik olamayan istatistikleri kullanın.","Если полученный профиль воздействия указывает, что данные мониторинга логнормального или нормального распределения не подходят, рекомендуется использовать непараметрическую статистику.","ばく露分布の解析の結果，サンプル値が対数正規分布や正規分布でないであろうとされる場合は，ノンパラメトリック統計による解析を検討する．",{"$nulls":3},155,181,193,198,167,49,168,136,155,177,62,148,150,184,66,0]
[null,{"$f":"Translation(D68,trad,Language)","v":"est. AM = arithmetic mean of a lognormal distribution\nestimated by the Minimum Variance Unbiased Estimate (MVUE), usually more accurate than the simple arithmetic mean of the data.\nThe arithmetic mean is the appropriate parameter for evaluating long term risk."},null,57,"comm.\nConcept","est. AM = arithmetic mean of a lognormal distribution\nestimated by the Minimum Variance Unbiased Estimate (MVUE), usually more accurate than the simple arithmetic mean of the data.\nThe arithmetic mean is the appropriate parameter for evaluating long term risk.","MA est = Media aritmética de una distribución log-normal estimada por el método Varianza Minima Estimada No-sesgada (VMEN-S), usualmente más precisa que la Media Aritmética simple. La media Aritmética es el parámetro correcto para evaluar la exposición a largo plazo.","MA est. = moyenne arithmétique d'une distribution log-normale,  estimée par la méthode dite sans biais et de variance minimale (MVUE), généralement plus exacte que la moyenne arithmétique simple des données. La moyenne arithmétique est le paramètre approprié pour estimer le risque à long terme.","est. AM = arithmetischer Mittelwert einer logarithmischen Normalverteilung berechnet mit Hilfe des erwartungstreuen Schätzer mit kleinster Varianz (MVUE), gewöhnlich genauer als der einfache arithmetische Mittelwert der Daten. Das arithmetische Mittelwert ist der entsprechende Parameter zur Beurteilung des Langzeitrisikos. ","MA est.= stimatore della media aritmetica di una distribuzione log-normale, stimato attraverso il metodo dello stimatore corretto di varianza minima (dall'inglese Minimum Variance Unbiased Estimator MVUE), generalmente piu' esatto che la semplice media aritmetica dei dati. La media aritmetica é il parametro appropriato per stimare un rischio a lungo termine","est. MA = 通过最小方差无偏估计（MVUE）得到一个对数正态分布的算术均数， 通常该算术均数比简单的算术均数要准确。当对长期的危险度进行评价时，适合使用算术均数。","MA Est.= média aritmética de uma distribuição lognormal estimada pela Variância Mínima Estimada Imparcial (VMEI), geralmente mais precisa do que a média aritmética simples de dados. \nA média aritmética é o parâmetro adequado para avaliar um risco de longo prazo.","odh. AP = aritmetický průměr log-normální distribuce odhadnutý z Minimum Variance Unbiased Estimate (MVUE), obvykle více přesný než jednoduchý aritmetický průměr dat. Aritmetický průměr je vhodný parametr pro hodnocení dlouhodobého rizika.","अनुमानित एएम = बिनपक्षपाती अनुमान न्यूनतम विचलन (एमवीयुइ) द्वारा अनुमानित लोग नोर्मल वितरण का गाणितिक मध्य, जो कि डाटा के सादे गाणितिक मध्य से अधिक सटीक है.\nदीर्घावधि जोखिम के मूल्यांकन के लिए गाणितिक मध्य सर्वोचित मानदंड है.","RG ges. = rekenkundig gemiddelde van een lognormale verdeling geschat door de Minimum Varantie Onververvalste Schatter (MVOS), vaak accurater dan het gewone rekenkundige gemiddelde van de meetgegevens. Het RG is de geschikte parameter om het lange termijn risico te evalueren.","추정 산술 평균= 최소분산 불평추정값(MVUE)으로 추정된 로그정규분포의 산술평균은 단순한 산술평균보다 일반적으로 더 정확합니다. 산술 평균은 장기적 위험을 평가하기위한 적합한 매개변수입니다.","Est AG = aritmetisk gjennomsnitt av en lognormal distribusjon anslått av Minimum varians forventningsrett estimat (MVUE), vanligvis mer nøyaktig enn den enkle aritmetiske gjennomsnitt av data. Det aritmetiske gjennomsnittet er riktig parameter for å vurdere langsiktig risiko.","tahmini AO = lognormal dağılımın aritmetik ortalaması\nMinimum Varyans Yansız Tahmini (MVUE) genellikle basit aritmetik ortalamadan daha doğrudur. \nAritmetik ortalama uzun vadeli riskleri hesaplamak için uygun bir parametredir. ","Оценка СА= Среднее Арифметическое значение логнормального распределения  вычисляемого помощью  Несмещённой Оценки с Минимальной Дисперсией, обычно более точно, чем просто средняя арифметическая  величина собранных данных. Использование среднего арифметического  более уместно для оценки риска на долгий срок.","算術平均値の推定値。対数正規分布をもとに最小分散不偏推定（MVUE）によって推定された算術平均値の推定値で，データの単純な算術平均値より一般的に正確である．算術平均値は長期の健康リスクの評価に適した変数である．",{"$nulls":3},260,267,295,325,359,85,262,239,225,276,107,276,227,308,105,0]
[null,"LCL1, 95%; Lower confidence limit on the estimated arithmetic mean - Land's exact;\nLand's exact method provides the most accurate\nconfidence interval for the estimate of the arithmetic mean. The combination of LCL95% and UCL95% forms a 90% confidence interval around the AM estimate.",null,58,"comm.\nConcept","LCL1, 95%; Lower confidence limit on the estimated arithmetic mean - Land's exact;\nLand's exact method provides the most accurate\nconfidence interval for the estimate of the arithmetic mean. The combination of LCL95% and UCL95% forms a 90% confidence interval around the AM estimate.","LCI1, 95%; Límite de Confianza Inferior de la media aritmética - Land's exacto; el método Land's exacto provee la estimación más precisa del intervalo de confianza. La combinación de LCI95% y el LCS95% conforman un intervalo de confianza de 90% alrededor de la media aritmética. ","LC inf. 1,95%; limite de confiance inférieure sur la moyenne arithmétique - Méthode \"exacte\" de Land; la méthode de Land fournit l'intervalle de confiance le plus exact autour de l'estimé de la moyenne arithmétique.  La combinaison des deux limites de confiances LCinf 95% et LCsup 95% forme un intervalle de confiance à 90% autour de l'estimé de la moyenne arithmétique","UKG, 95%; Untere Konfidenzgrenze für das geschätzte arithmetische Mittelwert - Lands \"genaue\" Methode; Lands \"genaue\" Methode bietet einen der genausten Konfidenzintervall für die Schätzung des arithmetischen Mittelwertes. Die Bindung der UKG95% und der OKG95% bildet einen 90%-Konfidenzintervall um den geschätzten AM.","LC inf. 1,95%; limite inferiore dell'intervallo di confidenza per la media aritmetica - Metodo \"esatto\" di Land; il metodo \"esatto\" di Land fornisce l'intervallo di confidenza piu' preciso per lo stimatore della media aritmetica. La combinazione dei due limiti di confidenza LCinf 95% e LCsup 95% definisce un intervallo di confidenza del 90% intorno al valore stimato per la media aritmetica","LCL，95%；估计的算术均数的可信限下限 - Land‘s 确切法。 Land's 确切法能够对算术均数的估计提供最准确的可信区间。结合LCL95%和UCL95%可以得到AM估计值的90%的可信区间。","LCI 1,95%; Limite de Confiança Inferior da média aritmética estimada - Land's exato; \nO método \"Land's exato\" fornece o Intervalo de confiança mais preciso para a média aritmética. A combinação de LCI 95% e LCS 95% define um intervalo de confiança de 90% em torno da MA estimada.","LCL1, 95%; Dolní hranice spolehlivovosti pro odhad aritmetického průměru byla nejpřesněji určena metodou podle Landa. Kombinace LCL95% and UCL95% tvoří 90% interval spolehlivosti pro odhad AP. ","एलसीएल1, 95% ; अनुमानित गाणितिक मध्य पर न्यूनतम विश्वास सीमा - भूमि का वास्तविक;\nभूमि का वास्तविक रीति, गाणितिक मध्य के अनुमान के लिए सटीक विश्वास अंतर उपलब्ध करवाती है.\nएलसीएल95% तथा युसीएल95% का संयोग एएम अनुमान के नजदीक का 90% विश्वास अंतर दिखाता है.","OBL1, 95%; Onderste BetrouwbaarheidsLimiet op het geschatte rekenkundig gemiddelde (RG) - Land's exact; Land's exacte test levert het meest accurate betrouwbaarheidsinterval (BI) op de schatting van het RG. De combinatie van OBL1, 95% en BBL1, 95% vormt een 90% BI rondom het geschatte RG.","신뢰하한1, 95%; 추정산술평균에 대한 신뢰하한-Land's 정확성; Land's 정확성 방법은 산술 평균의 추정을 위해 가장 정확한 신뢰 구간을 제공합니다. 신뢰하한95%와 신뢰상한95%의 조합은 산술평균 추정 부근의 90% 신뢰 구간을 형성합니다.","NKG1, 95%, Nedre konfidensgrense av det estimert aritmetiskgjennomsnitt - Land's exact; Land's exact metode gir det mest nøyaktige konfidensintervall for estimering av aritmetiskgjennomsnitt. Kombinasjonen av NKG95% og ØKG95% danner et 90% konfidensintervall rundt estimaet av AG. ","LCL1,% 95; tahmini aritmetik ortalama ile ilgili alt güven sınırı - Land's kesin;\nLand's kesin methodu aritmetik ortalama (AM) tahmini için en doğru güven aralığını sağlar. %95  LCL ve %95 UCL kombinasyonu tahmin edilen AM etrafında % 90 güven aralığı oluşturur.","НДП 1,95% ; Нижний Доверительный Предел на расчитанное значение арифметического среднего называется точное значение Лэнда. Метод точного значения Лэнда предоставляетсобой самый точный доверительный интервал на расчитанное среднее арифмитическое . Сочетание НДП  95% и ВДП 95% дают 90% интервал уверенности около расчитанного СА .","LCL1,95%；算術平均値の推定値の片側95%信頼区間の下限値．\nLandの正確法；この方法は算術平均値の推定値の最も正確な信頼区間を与える．\nLCL95%とUCL95%は算術平均値の上下90%の信頼区間を形成する．",{"$nulls":3},{"$f":"LEN(F69)","v":283},{"$f":"LEN(G69)","v":279},{"$f":"LEN(H69)","v":370},{"$f":"LEN(I69)","v":319},{"$f":"LEN(J69)","v":392},{"$f":"LEN(K69)","v":101},{"$f":"LEN(L69)","v":279},{"$f":"LEN(M69)","v":193},{"$f":"LEN(N69)","v":253},{"$f":"LEN(O69)","v":289},{"$f":"LEN(P69)","v":141},{"$f":"LEN(Q69)","v":281},{"$f":"LEN(R69)","v":262},{"$f":"LEN(S69)","v":329},{"$f":"LEN(T69)","v":109},{"$f":"LEN(U69)","v":0}]
[null,"If the arithmetic mean's one sided 95% upper\nconfidence limit(UCL,1,95%) is below the OEL, one\nwould be at least 95% sure that the exposure\nprofile's arithmetic mean is below the OEL.",null,59,"comm.\nConcept","If the arithmetic mean's one sided 95% upper\nconfidence limit(UCL,1,95%) is below the OEL, one\nwould be at least 95% sure that the exposure\nprofile's arithmetic mean is below the OEL.","Si se calcula el límite superior de confianza en 95% (UCL,1,95%) de la media aritmética y se encuentra por debajo del LEO, el higienista puede estar al menos 95 % seguro que el perfil de exposición es menor que el LEO.","Si la limite de confiance supérieure à 95% (unilatérale) sur la moyenne arithmétique est inférieure à la VLE, on est assuré qu'il y a au moins 95 % de chances que la moyenne arithmétique du profil d'exposition est inférieure à la VLE.","Wenn die obere 95%-Konfidenzgrenze des arithmetischen Mittelwertes (einseitig) kleiner ist als das MAK, dann ist man zu wenigstens 95% sicher dass das Expositionsprofil des arithmetischen Mittelwertes unter dem MAK liegt.","Se il limite superiore dell'intervallo di confidenza al 95% (unilaterale) per la media aritmetica é inferiore al valore di soglia (TLV), il profilo d'esposizione sarà inferiore al valore di soglia con probabilità 95%","如果该算术均数的95%的可信区间上限（UCL，1，95%）低于OEL，我们就至少有95%把握认为该接触资料的算术均数低于OEL。","Se o Limite Superior de Confiança unilateral em 95% (LSC, 1,95%) da média aritmética está abaixo do LEO, poderíamos, no mínimo, ter 95% de certeza de que a média aritmética do perfil de exposição está abaixo do LEO.","Jestliže 95% horní hranice spolehlivosti aritmetického průměru  (UCL, 1 ,95%) je pod EL, je z 95% jisté, že aritmetický průměr expozičního profilu je pod EL.","यदि गाणितिक मध्य का एकतरफी 95% उच्चतर विश्वास सीमा (युसीएल1, 95%), ओइएल से कम है, तो कोई भी 95% इतना तय कर सकता है कि एक्स्पोजर प्रोफाईल का गाणितिक मध्य ओइएल से कम है.","Als de eenzijdige 95% Bovenste BetrouwbaarheidsLimiet (BBL,1,95%) van het rekenkundig gemiddelde (RG) onder de GBB ligt, dan zijn we ten minste 95% zeker dat het RG van het blootstellingsprofiel onder de GBB ligt.","산술 평균의 단측 95% 신뢰상한(신뢰상한1, 95%)이 직업노출기준 이하라면, 노출 개요서의 산술평균이 직업노출기준 이하임을 최소한  95% 확신할 수 있습니다.","Hvis det aritmetiskgjennomsnittets ensidig 95% øvre konfidensgrense (ØKG, 1,95%) er under YGV, vil minst 95% for at eksponeringsprofilens aritmetiskgjennomsnitt være under YGV.","Eğer aritmetik ortalamanın tek taraflı % 95 üst güven sınırı (UCL, 1,95%) OEL altında ise, maruziyet profili aritmetik ortalaması en az %95 olması beklenir ki bu değer OEL altındadır. ","Если СА односторонне   95% ВДП (1,95%) и ниже заданного ЛПО, тогда  есть 95% уверенности, что СА данного профиля воздействия вещества будет ниже ЛПО.","もし，算術平均値の片側95%信頼区間の上限値(UCL,1,95%)がばく露限界値未満の場合，ばく露分布の（真の）算術平均値がばく露限界値未満であることが少なくとも95%の確率で言えることになる．",{"$nulls":3},183,218,234,221,216,64,215,157,167,213,91,176,184,149,97,0]
[null,"The 95th percentile point estimate. The 95th percentile, to which 95% of the distribution is inferior, provides a \"picture\" of the exposure profile's upper tail and is especially important when evaluating the health hazard of agents with acute health effects (such as hydrogen cyanide) or when evaluating the risk of non compliance to an OEL. In the case of an acute agent, the average exposure is not as important as understanding how high the exposure may get because those few high exposures might pose a more important risk to health than average exposures at lower levels.  However, there is uncertainty associated with the percentile estimate - that uncertainty can be evaluated by calculating an upper tolerance limit.",null,60,"comm.\nConcept","The 95th percentile point estimate. The 95th percentile, to which 95% of the distribution is inferior, provides a \"picture\" of the exposure profile's upper tail and is especially important when evaluating the health hazard of agents with acute health effects (such as hydrogen cyanide) or when evaluating the risk of non compliance to an OEL. In the case of an acute agent, the average exposure is not as important as understanding how high the exposure may get because those few high exposures might pose a more important risk to health than average exposures at lower levels.  However, there is uncertainty associated with the percentile estimate - that uncertainty can be evaluated by calculating an upper tolerance limit.","Estimación del percentil 95 del perfil de exposición. Es el percentil en el cual el 95% es inferior, forma un imagen de la región superior de la distribución. Es particularmente importante para la evaluación de riesgos asociados a ganetes con efectos agudos para la salud (como el cianuro de hidrógeno) o para evaluar el riesgo de no-conformidad de un LEO. En el caso de los agentes agudos, las exposiciones elevadas transitorias tiene mayor riesgo de afectar la salud que la exposición promedio a concentraciones más bajas. Sin embargo, hay incertidumbre en la estimación del percentil, la cual puede ser evaluada calculando el límite de toleracia superior LTS. ","L'estimé du 95e percentile du profil d'exposition. Ce percentile, auquel 95% des valeurs du profil sont inférieures, fournit une image de la région supérieure de la distribution. Il est particulièrement important lors de l'évaluation du risque associé à des agents ayant des effets aigus sur la santé (tel que le cyanure d'hydrogène) ou pour estimer le risque de non-conformité à une VLE. Dans le cas d'un agent ayant des effets aigus, des expositions élevées transitoires sont plus à risque d'affecter la santé qu'une exposition moyenne à une concentration plus basse. Il y a cependant une incertitude liée à l'estimation des percentiles, incertitude que l'on évalue en calculant une limite supérieure de tolérance.","Die 95. Perzentile Punktschätzung. Die 95. Perzentile, dem 95% der Werte der Verteilung kleiner ist, bietet ein \"Bild\" des oberen Gebietes des Expositionsprofils. Sie ist äusserst wichtig bei der Risikobeurteilung von Wirkstoffen mit akuten Wirkungen für die Gesundheit (wie z.B. der Cyanwasserstoff) oder bei der Risikoeinschätzung einer Nichtübereinstimmung der MAK. Im Falle eines Wirkstoffes mit akuten Wirkungen für die Gesundheit ist die Durchschnittsexposition nicht so wichtig als die Einsicht wie hoch eine Exposition werden kann, weil diese wenigen hohen Expositionen können ein bedeutenderes Risiko hervorrufen als Durchschnittsexpositionen mit niedrigeren Konzentrationen. Allerdings gibt es eine Unsicherheit mit der 95. Perzentile Punktschätzung - diese Unsicherheit kann mit dem Rechnen einer oberen Toleranzgrenze geschätzt werden. ","Il 95simo percentile stimato del profilo d'esposizione. Il 95simo percentile, punto al di sotto del quale si trova il 95% dei valori d'un profilo, fornisce un'immagine della regione superiore della distribuzione. É particolarmente importante per la valutazione del rischio correlato all'esposizione a sostanze aventi effetto acuto sulla salute (come il cianuro di idrogeno) o per stimare il rischio di non conformità rispetto al limite di soglia (TLV). Nel caso di sostanze aventi un effetto acuto, una breve esposizione a picchi di concentrazione puo' avere un rischio piu' importante che una piu' lunga esposizione a un livello medio piu' basso. Esiste comunque un'incertezza legata alla stima dei percentili, incertezza che si puo' valutare calcolando un limite superiore di tolleranza.","第95百分位点估计值。第95百分位数，如果分布的第95百分位数要低于OEL，那么就提供了一个接触资料的上尾的\"图形\"轮廓，而且在评价具有急性健康效应的化学物质（如氰化氢）的健康危害时或者评价不满足OEL的危险度是非常重要的。但是对于具有急性毒性的物质而言，峰值水平比平均接触水平更重要，因为偶尔的高浓度的接触可能会比更低的平均接触水平导致更严重的健康效应。但是该百分位数估计也存在不确定性，该不确定性可以通过计算容许限值的上限来进行评价。","Estimativa do ponto de percentil 95. O percentil 95, para o qual 95% da distribuição é inferior, fornece uma \"foto\" do perfil da cauda superior do perfil de exposição e é especialmente importante quando se avaliam os riscos à saúde pela exposição a agentes químicos com efeitos agudos à saúde (tal como cianeto de hidrogênio) ou quando se avalia o risco de não-conformidade a um LEO. No caso de um agente químico com efeitos agudos, a média da exposição não é tão importante quanto a compreensão do quão alta pode ser a exposição, pois essas poucas altas exposições podem representar um risco mais importante à saúde do que a exposição média a níveis mais baixos. Entretanto, existe uma incerteza associada à estimativa do percentil - incerteza que pode ser avaliada calculando-se o limite de tolerância superior.","Odhad 95. percentilu. 95. percentil, jehož hodnota zahrnuje 95% distribuce dat, poskytuje \"obraz\" horního konce expozičního profilu a je zvláště důležitý v případě hodnocení zdravotního rizika činitelů, majících akutní vliv na zdraví (například kyanovodík) nebo při hodnocení rizika nesplnění požadavků EL. V případě látky působící akutním účinkem je významný především údaj o nárazových krátkodobých koncentracích (méně významný je údaj o průměrných expozicích). Omezené krátkodobé vysoké expozice mohou představovat vyšší riziko než průměrné expozice nižším dávkám. Je ovšem nutno počítat s nejistou odhadu percentilu - tato nejistota může být vyhodocena výpočtem horního tolerančního limitu.","95वें प्रतिशत पाइन्ट अनुमान. 95वें प्रतिशत पाइन्ट अनुमान, जिससे वितरण का 95% निम्न होता है, एक्सपोजर प्रोफाइल की ऊपरी सीमा का चित्र देता है और एक्युट स्वास्थ्य प्रभाव वाले एजेन्टों के स्वास्थ्य जोखिमों की गणना या ओइएल पर अननुपालन के जोखिम की गणना के समय यह विशेष रूप से आवश्यक है. एक्युट एजेन्ट के मामले में, औसत एक्स्पोजर उतना महत्वपूर्ण नहीं है जितना कि यह जानना कि एक्स्पोजर कितना ऊंचा रहेगा, क्योंकि इन कुछ उच्च एक्स्पोजर, कम स्तरों पर रहे औसत एक्स्पोजरों की तुलना में स्वास्थ्य पर अधिक जोखिम सृजित करता है. हालांकि, प्रतिशत अनुमान से अनिश्चितता जुडी है - हि उच्चतर सह्यता सीमा के गणन द्वारा अनिश्चितता का मूल्यांकन किया जा सकता है.","De puntschatting van het 95ste Percentiel. De 95ste Percentiel (95% van de verdeling ligt onder deze waarde) levert een beeld van de bovenste staart van het blootstellingsprofiel en is van bijzonder belang in het evalueren van de gevaren van agentia met acute gezondheidseffecten (zoals waterstofcyanide) of het evaleren van het risico om niet aan de GBB te voldoen. In het geval van een acuut agens is de gemiddelde blootstelling lang niet zo belangrijk als begrijpen hoe hoog de blootstelling zou kunnen  worden, omdat die enkele hoge blootstellingen een belangrijker risico voor de gezondheid kunnen vormen dan gemiddelde blootstellingen in lagere concentraties. Er is echter onzekerheid verbonden aan deze puntschatting. Deze onzekerheid kan geëvalueerd worden door een Bovenste Tolerantie Limiet (BTL) te berekenen.","95번째 백분위 점 추정치. 분포의 95 %가 하한인 95번째 백분위는 노출 개요서의 상한꼬리에 \"그림\"을 제공하며 급성건강영향 (예를 들어 시안화 수소)을 미치는 건강 유해요소를 평가할때나 직업노출기준에 비준수 위험을 평가할때 특히 중요합니다. 급성요소인 경우, 이러한 몇몇의 높은 노출이 낮은 수준에서 평균 노출보다 건강에 더 중요한 위험을 일으킬 수 있기 때문에 평균 노출은 얼마나 노출수준이 높은가의 개념만큼 중요하지 않습니다. 그러나 백분율 추정과 관련된 불확실성이 있습니다 - 그 불확실성은 상위 허용 한계를 계산하여 평가할 수 있습니다.","Punkt estimatet for 95 persentilen. 95-persentilen, hvor 95% av distribusjonen er dårligere, gir et \"bilde\" av eksponeringsprofilens øvrehale og er spesielt viktig når man skal vurdere helsefare av knyttet til eksponering for stoffer med akutte helseeffekter (for eksempel hydrogen cyanid) eller når skal vurderes sannsynlighet for manglende samsvar med yrkeshygieniske grenseverdier (YGV). I tilfelle av en akutt effekt, er den gjennomsnittlige eksponeringen ikke så viktig, som å forstå hvor høy eksponering kan bli, fordi de få høy eksponeringene kan utgjøre en mer viktig helserisiko enn gjennomsnittseksponeringen ved lavere nivåer. Det er imidlertid usikkerhet knyttet til persentil estimatet - denne usikkerheten kan vurderes ved å beregne en øvre toleransegrense (ØTG).","95'lik yüzde dilim tahmini. %95'lik yüzdelik dilim, % 95'lik dağılımın altıdır, maruziyet profilinin üst-kuyruk kısmına ait \"resim\" sağlar ve bu bilgi ajanların akut sağlık etkileri (hidrojen siyanür gibi)  ile birlikte sağlık tehlikesini değerlendirirken veya OEL ile uyumlu olmayan riski değerlendirirken çok önemlidir. Akut ajan durumunda, ortalama maruziyetyüksek maruziyetin nasıl oluştuğunun anlaşılması kadar önemli değildir çünkü bazı yüksek maruziyetler düşük seviyelerdeki ortalama maruziyetlere oranla sağlığa daha riskli olabilir. Ancak, yüzde tahmini ile ilgili belirsizlik var - bu belirsizlik bir üst tolerans sınırı hesaplanarak değerlendirilebilir.","95%-й процентиль -  это значение меньше которого  95% наблюдений предоставляет отличную картину верхнего хвоста сбранных данных воздействия. Это особенно важно при оценки опасности для здоровья очень вредного вещества с тяжелыми последствиями для здоровья (например синильная к-та), или когда оценка риска  не согласовывается с ЛПО. В случае оценки очень вредного вещества, значение усредненного воздействия вещества менее важно, нежели информация о самой высокой возможной концентрации, так как именно это несет серьезные негативные последствия для здоровья.   Тем не менее, существует неопределенность, связанная с оценкой процентиля, и эта неопределенность может быть расчитана путем подсчета верхнего допустимого предела.","95パーセンタイル値の点推定値．95パーセンタイル値とは，分布の95%のデータがその値より小さい値のことで，ばく露分布の上端を「象徴」する値であり，急性の健康影響を持つ物質（シアン化水素等）の評価や，OELを超える過剰ばく露リスクの評価に殊に重要である．急性影響物質の場合，時々起きる高いばく露がそれより低い定常的なばく露よりも高い健康リスクとなることから考えて，ばく露の平均値は，ばく露が時として如何に高くなるかということより重要性が低い．なお，95パーセンタイルの推定には不確実性が伴い，それは上側許容区間の算出により評価できる．",{"$nulls":3},725,663,716,848,789,219,813,694,636,820,307,777,665,725,267,0]
[null,"The upper limit of a tolerance interval. This parameter can be viewed as an upper confidence limit on the 95th percentile.  Thus, we are 95% confident that at least 95% of the distribution are inferior to the UTL1,95%,95% estimate",null,61,"comm.\nConcept","The upper limit of a tolerance interval. This parameter can be viewed as an upper confidence limit on the 95th percentile.  Thus, we are 95% confident that at least 95% of the distribution are inferior to the UTL1,95%,95% estimate","Límite superior de un intervalo de tolerancia. Este parámetro puede interpretarse como el Límite de Confianza Superior. Por tanto, tenemos 95% de confianza que por lo menos el 95% de la distribución es inferior al LTS, 95%, 95% estimado.","La limite supérieure d'un intervalle de tolérance. La limite de tolérance permet de quantifier la confiance dans l'estimation d'un percentile. Ainsi, on peut être certain à 95 % qu'au moins 95% des valeurs du profil sont inférieures à l'estimé de LTsup1 ,95%,95%","Die obere Grenze eines Toleranzintervalls. Dieser Parameter kann als eine obere Konfidenzgrenze des 95. Perzentiles angesehen werden. Daher können wir mit 95 % sicher sein dass wenigstens 95% der Verteilung kleiner sind als die geschätzte OTG, 95%, 95%.","Il limite superiore dell'intervallo di tolleranza. Il limite di tolleranza permette di valutare la confidenza della stima di un percentile. Quindi possiamo essere certi al 95% che almeno il 95% dei valori di un profilo sono inferiori al limite superiore LTsup. 1.95%,95%","容许区间的上限。该参数可以看作是在第95百分位上的可信区间的上限。因此，我们有95%的信心认为该分布至少有95%是低于UTL1,95%,第95%点估计值的。","Limite superior de um intervalo de tolerância. Este parâmetro pode ser visto como um limite superior de confiança do percentil 95. Assim, temos a confiança de que pelo menos 95% da distribuição é inferior ao LTS 1,95%, estimativa de 95%","Horní limit tolerančního intervalu. Tento parametr může být prezentován jako horní limit spolehlivosti na 95. percentilu, kde máme 95% jistotu, že minimálně 95% distribuce dat je pod UTL1,95%, 95% odhadu.","सह्यता अंतर की ऊपरी सीमा. इस मानदंड को 95वें प्रतिशत पर उच्चतर विश्वास सीमा के रूप में देख सकते हैं. इस तरह, हम 95% आश्वस्त होते हैं कि वितरण का कम से कम 95% युटीएल1, 95%, 95% से निम्न है; ","De bovenste limiet van een tolerantie interval. Deze parameter kan beschouwd worden als een bovenste betrouwbaarheidslimiet op een 95ste Percentiel. We zijn dus 95% zeker dat ten minste 95% van de verdeling onder de BTL1,95%,95% schatting valt.","허용구간의 상한. 이 매개변수는 95번째 백분위에서 신뢰상한으로 볼 수 있습니다. 따라서, 최소한 95%의 분포가 상위허용관계1, 95%, 95% 추정치보다 하한임을 95% 확신할 수 있습니다.","Den øvre grensen for et toleranse-intervall. Denne parameteren kan sees på som en øvre konfidens grense til 95-persentilen. Dermed er vi 95% sikre på at minst 95% av fordelingen er lavere enn ØTG1, 95%, 95% estimatet.","Tolerans aralığının üst limiti. Bu parametre, 95. persentilde üst güven sınırı olarak görülebilir. Böylece, %95 güvenilirlik elde edilmiş olunur ki dağılımın %95'i en az %95 tahminle %95 UTL1'in altında kalır. ","Верхний Предел Допустимого Интервала. Этот параметр может быть рассмотрен как Верхний Доверительный Предел  95го перцентиля. Это значит, что мы  на 95% уверены что хотя бы 95% распределения ниже  Верхнего Предела Допустимого Интервала 1,95% на расчитанные 95%.","許容区間の上限値．この値は95パーセンタイル値の（片側）95%信頼区間の上限値に相当する．この場合，ばく露分布の少なくとも95%がUTL1,95%より小さいことが95%の信頼性をもって言えることになる．",{"$nulls":3},230,237,262,253,270,78,236,204,189,244,108,217,210,260,101,0]
[null,"Exceedance Fraction; it is the proportion of the exposure\nprofile that exceeds the OEL. Occupational exposure guidelines are established so that with\nhighest certainty permitted by available data most workers will\nnot suffer health effects if exposed at the guideline level, day\nafter day for a working lifetime. Implicit in that description is\nthe possibility that a small fraction may indeed experience health\neffects at or below the guideline level. This one reason why all\nexposures should be kept as far below guidelines level as\nreasonably achievable. Because of the inherent variability of\nworkplace concentrations, guaranteeing that all exposures\nare below a guideline is impossible. Demonstrating statistically\nthat no more than a given percentage are greater than a standard\nhowever is possible. This notion is the basis for a exceedance fraction test. The uncertainty in the exceedance fraction point estimate is delimited by calculating a confidence interval.\n",null,62,"comm.\nConcept","Exceedance Fraction; it is the proportion of the exposure\nprofile that exceeds the OEL. Occupational exposure guidelines are established so that with\nhighest certainty permitted by available data most workers will\nnot suffer health effects if exposed at the guideline level, day\nafter day for a working lifetime. Implicit in that description is\nthe possibility that a small fraction may indeed experience health\neffects at or below the guideline level. This one reason why all\nexposures should be kept as far below guidelines level as\nreasonably achievable. Because of the inherent variability of\nworkplace concentrations, guaranteeing that all exposures\nare below a guideline is impossible. Demonstrating statistically\nthat no more than a given percentage are greater than a standard\nhowever is possible. This notion is the basis for a exceedance fraction test. The uncertainty in the exceedance fraction point estimate is delimited by calculating a confidence interval.\n","Fracción excedente: es la proporción del perfil de exposición que excede el valor criterio como el LEO. Los valores límites de exposición en el lugar de trabajo son establecidos de manera que con la mayor certeza posible se protege la salud de la mayoría de los trabajadores expuestos a esa concentración día a día, durante su vida laboral activa. Queda implícita la probabilidad de que alguna proporcion de trabajadores pueda tener efectos sobre su salud a concentraciones iguales o inferiores al LEO. Es por esta razon que las exposiciones deben mantenerse a los niveles más bajos posibles. Es imposible garantizar que todas las concentraciones estén por debajo del LEO debido a la variabilidad inherente de las concentraciones en el lugar de trabajo. Por tanto, es posible demostrar estadísticamente que no más de cierto porcentaje es mayor del estándar. Esta es la base de la estimaciòn de la fracción excedente. La incertidumbre de la fracción excedente estimada se delimita mediante el cálculo de los límites de confianza. ","Fraction de dépassement; c'est la proportion des valeurs du profil d'exposition qui dépassent la VLE. Les valeurs limites d'exposition en milieu de travail sont établies en fonction des connaissances disponibles et permettent que la santé de la majorité des travailleurs soit protégée s'ils sont exposés jusqu'à de telles concentrations, jour après jour durant toute leur vie active. Cette définition sous-entend qu'un faible nombre de travailleurs pourront subir des effets à une concentration égale ou inférieure à ces valeurs. Pour cette raison, les expositions doivent être maintenues aussi basses que possible. Vu la variabilité dans les concentrations mesurées dans un milieu de travail, il est impossible de garantir que toutes les expositions sont inférieures aux VLE. Il est cependant possible de démontrer statistiquement que pas plus d'un certain pourcentage leur sera supérieur. Cette notion est à la base de l'estimation de la fraction de dépassement. L'incertitude associée à l'estimé de la fraction de dépassement est déterminée par le calcul d'un intervalle de confiance.","Überschreitungsanteil: es ist der Anteil des Expositionsprofils der die MAK überschreitet. Es gibt Richtlinien für die Expositionen auf dem Arbeitsplatz so dass die meisten Arbeiter, mit höchster Sicherheit erlaubt durch gültigen Daten, nicht an Gesundheitsschäden leiden werden, wenn sie an der MAK ausgesetzt sind, Tag für Tag während dem ganzen Arbeitsleben. Diese Bezeichnung ergibt die Möglichkeit dass ein kleiner Anteil allerdings an Gesundheitsschäden erleiden kann wenn dem MAK-Wert oder unter dem MAK-Wert ausgesetzt sind. Deswegen sollten die Expositionen so niedrig wie möglich gehalten werden. Da es eine gewisse Variabilität von den Konzentrationen auf dem Arbeitsplatz gibt, ist es unmöglich sicherzustellen dass alle Expositionen unter den MAK-Werten bleiben. Allerdings ist es möglich statistisch zu beweisen dass nicht mehr als einen gewissen Anteil über den MAK-Werten liegt. Diese Kenntnis ist die Basis für einen Überschreitungsanteiltest. Die Unsicherheit der Punktschätzung des Überschreitungsanteils ist durch das Rechnen eines Konfidenzintervalls begrenzt.","Frazione eccedente: rappresenta la percentuale dei valori di un profilo superiori al valore limite di soglia (TLV). I valori limite di esposizione sono fissati in modo tale che  la maggior parte dei lavoratori possa rimanere esposta ripetutamente giorno per giorno senza effetti negativi per la salute, per tutta la durata della vita lavorativa. In questa definizione é implicita la possibilità che una ridotta percentuale di lavoratori possa presentare effetti anche a livelli d'esposizione inferiore al limite di soglia. Per questo motivo l'esposizione deve essere mantenuta ai livelli piu' bassi possibili. Data la variabilità delle concentrazioni misurate negli ambienti lavorativi, garantire che tutte le esposizioni siano inferiori al limite raccomandato é impossibile. Resta comunqe possibile dimostrare statisticamente che non piu' di una certa percentuale sarà superiore. Questo concetto é alla base della stima della frazione eccedente. L'incertezza associata alla stima della frazione eccedente é determinata grazie all'intervallo di confidenza.","超标比例；这是接触监测数据中超过OEL水平的部分。建立职业性接触标准的目的就是为了根据现有的资料在最大程度上保护绝大多数的工人在其整个工作生命期间每天反复接触该浓度时不会受到健康危害。该定义也暗示了允许一小部分的工人在接触低于或者等于该标准浓度的情况下会引起健康危害。这也是要求所有的接触浓度在可以达到的情况下必须尽可能地保持在低于标准水平的原因之一。由于工作场所中浓度的变化，要保证所有的接触浓度低于标准是不可能的。但是要在统计学上表明一定百分比的接触浓度不超过标准还是可行的。这就是超标比例检验的基础。超标比例点估计值的不确定性可以通过计算可信区间来进行界定。","Fração Excedente; é a porção do perfil de exposição que ultrapassa o LEO. As diretrizes sobre exposição ocupacional são estabelecidas a fim de que, com a mais alta certeza permitida pelos dados disponíveis, a maioria dos trabalhadores não sofrerão efeitos adversos a saúde quando expostos aos níveis recomendados, dia após dia ao longo de sua vida laboral. Está implícito nessa descrição de que existe a possibilidade de que uma pequena fração dos trabalhadores podem, de fato, experimentar efeitos adversos à sua saúde em exposições ao nível ou mesmo abaixo desse valor de referência. Esta é uma das razões pela qual todas as exposições devem ser mantidas ao nível mais baixo possível do LEO, tanto quanto for razoavelmente exeqüível. Devido a variabilidade inerente às concentrações nos locais de trabalho é impossível garantir que todas as exposições estejam abaixo dos valores de referência. Entretanto, é possível demonstrar estatisticamente que, não mais que uma dada porcentagem é superior ao padrão. Este conceito é a base para o teste de fração excedente. A incerteza na estimativa do ponto de fração excedente é delimitado pelo cálculo de um intervalo de confiança.","Zlomek překročení; jedná se o část expozičního profilu která překračuje EL. Obecné zásady regulace expozice na pracovišti jsou upraveny tak aby při regulované každodenní celosměnové expozici nedocházelo u většiny pracovníků (s bezpečnostní rezervou) k zdravotním projevům přímo souvisejícím s touto expozicí. Z uvedeného popisu vyplývá, že i malý expoziční zlomek na regulované hladině nebo bezprostředně pod ní může zdravotní stav ovlivnit. Z tohoto důvodu by všechny expozice měly být udržovány co možná nejníže pod regulačními hladinami. Z důvodu inherentní variability koncentrací na pracovišti je garance, že všechny expozice budou pod stanovenými hladinami, prakticky nemožná. Statistický důkaz skutečnosti, že ne více než dané procento je vyšší než limit, je nicméně možné. Tento poznatek je základem pro test zlomku překročení. Nejistota odhadu  zlomku překročení je vymezena výpočtem intervalu spolehlivosti.","अनुमान आधिक्य अंश वह एक्स्पोजर प्रोफाइल का ऐसा अंश है जो ओइएल से अधिक होता है. व्यावसायिक एक्स्पोजर मार्गदर्शी सिध्दांत स्थापित किये गये हैं ताकि उपलब्ध डाटा द्वारा उच्चतर सटिकता संभव हो सके और यदि कार्यकाल के दौरान दिन-बदिन मार्गदर्शी स्तर तक एक्स्पोजर होता है तो भी अधिकाधिक कामदार स्वास्थ्य प्रभावों से प्रभावित न हों. इस विवरण में वह संभाव्यता निहित है कि छोटा अंश भी हकिकत में मार्गदर्शी स्तर तक या कम स्वास्थ्य प्रभाव का अनुभव करता है. इस एक कारण से ही सभी एक्स्पोजरों को मार्गदर्शी स्तर से कम रखना चाहिये जिससे उन तक पहुंचा जा सके. कार्यस्थान संकेन्द्रण की निहित चलनीयता के कारण यह गारंटी होती है कि सभी एक्स्पोजर मार्गदर्शी स्तर से कम हो यह संभव नहीं है. हालांकि, दिये गये प्रतिशत में से कोई मानक से अधिक नहीं है यह सांख्यिकीय रूप से दर्शाना संभव है. यह सिध्दांत आधिक्य अंश परीक्षण के लिए आधार रूप है. आधिक्य अंश पाइन्ट अनुमान में अनिश्चितता, विश्वास अंतर की गणना करके तय की जा सकती है.","Overschrijdingsfractie; de fractie van het blootstellingsprofiel die de GBB overschrijdt. Richtwaarden voor beroepsmatige blootstelling zijn -met de hoogste zekerheid die de beschikbare data toelaten- op deze manier opgesteld dat deze meeste werknemers geen gezondheidseffecten zullen ondervinden als ze aan deze richtwaarden worden blootgesteld, dag na dag, een heel werkleven lang. Hierom moeten alle blootstellingen zo ver mogelijk beneden de richtwaarden gehouden worden als redelijkerwijze mogelijk is. Door de inherente variabiliteit van werkplaatsatmosfeerconcentraties is garanderen dat alle concentraties beneden een richtwaarde zijn onmogelijk. Statistisch aantonen dat niet meer dan een bepaald percentage groter is dan een bepaalde standaard is wel mogelijk. Deze notie vormt de basis voor een overschijdingsfractie test. Aan de onzekerheid in de puntschatting van de overschrijdingsfractie wordt tegemoet gekomen door een betrouwbaarheidsinterval te berekenen.","초과율; 직업노출기준을 초과하는 노출 개요서의 비율입니다. 현재 나와 있는 데이터에서 가장 확실한 바를 따른 직업노출지침은, 지침 수치이하로  매일 직업평생동안 노출될 경우 대부분의 근로자들이 건강에 문제가 없도록 만들어진 것입니다. 이것은 곧 소수의 사람들은 지침에 나온 대로, 혹은 그 이하의 수치에 노출될 경우에도 건강에 영향을 받을 수도 있다는 것을 의미합니다. 이것이 왜 모든 데이터가 가능한 한 지침에 나온 수치이하로 유지되어야 하는가의 이유입니다. 작업장에 내재하는 농도의 변수 때문에 모든 노출이 지침이하를  보증할 수는 없습니다. 통계학적으로 기준치가 주어진 비율 이상으로 크지 않다는 것을 보이는 것은 가능합니다. 이 개념은 초과율 검증을 하기위한 기본이 됩니다. 초과율 점 추정의 불확실성은 신뢰구간을 계산하여 구분되어집니다.","Overskridelses fraksjon; er den andelen av eksponeringsprofilen som overstiger YGV. Tiltaks- og grenseverdier er etablert for vurdering av yrkeseksponering. Disse er basert på en vurdering av tekniske, helsemessige og samfunnsmessige forhold. Kun grenseverdiene er satt alene for å sikre at ett flertall av arbeidstakere ikke vil bli syke etter et arbeidslivs daglig eksponering for disse grenseverdiene. Andre helsebaserte verdier er f.eks. ACGIH sine TLV verdier. Grenseverdiene gir imidlertid ingen garanti for at ingen skal bli syk. Det er derfor grunn til å etterstrebe en eksponering som er så lav som mulig. På grunn av den iboende variasjon i eksponeringen på en arbeidsplass er det umulig å garantere at eksponeringen vil være under YGV. Det er imidlertid mulig statistisk å vise at en gitt prosentandel er større enn en YGV. Denne oppfatningen er grunnlaget for denne \"overskridelses testen\". Usikkerheten i overskridelsesfraksjonens punktestimatet er vurdert ved å beregne et konfidensintervall.","Aşım Kesri (Fraksiyonu); OEL değerini aşan maruziyet profilinin oranıdır. Mesleki maruz kılavuzları tanımlanmıştır böylece kullanılabilir veri ile elde edilen yüksek kesinlik bilgisi ile eğer çalışma süresince kılavuz değerlerde maruziyet olduğunda birçok çalışanda sağlık etkileri oluşmayacaktır. Bu açıklamada dolaylı olarak ifade edilen husus kılavuz değerde veya altındaki maruziyetlerde çok düşük oranda da olsa sağlık etkilerinin görülebileceğidir. Bu nedenle mümkün olabildiğince maruziyetlerin kılavuz değerlerin altında olması gerekmektedir.  İşyeri konsantrasyonlarının doğal değişkenliği nedeniyle tüm maruziyet değerlerinin kılavuz değerin altında olduğunu garantilemek mümkün değildir. İstatistiksel olarak gösterilmiştir ki belirlenen yüzdelikten daha çok değildir ancak standartdan daha yüksek olması mümkündür.  Bu durum aşılma kesri testinin temelidir. Aşım fraksiyonu nokta tahminindeki belirsizlik güven aralığı hesaplanması ile sınırlandırılır.","Фракция превышения - это пропорция собранных данных воздействия вещества, которая превышает данный ЛПО. Рекомендованный Профессиональный уровень облучения устанавливается таким образом, чтобы основываясь на имеющихся данных, с наивысшей точностью, можно предоставить защиту от токсичного влияния на здоровье подавляющему большинству рабочих в случае воздействия рекомендуемого уровня день за днем, ​​в течение рабочей жизни. Подразумевается, что малая   фракция вредного вещества может дать негативный эффект на здоровье, даже при коцентрации ниже рекомендованной. Это одна из причин, почему концентрация вредного вещества должна быть сведена до уровня ниже рекомендованного, если это возможно. Из-за присущей изменчивости концентрации на рабочем месте,  не возможно гарантировать, что все концентрации определенного вредного вещества будут ниже допустимой. Статистически возможно показать, что определенный процент концентраций больше, чем установленный предел. Это понятие является основой для теста фракции превышения. Неточность фракции превышения ограничена расчетом доверительного интервала.","超過割合ともいう．ばく露分布のうちばく露限界値を超えているものの割合．職業性ばく露のガイドラインは，ほとんどの労働者が一生涯の労働期間にわたって毎日基準濃度（ばく露限界値）にばく露しても健康影響を生じないということが，既存のデータに基づく最大限の確信をもって言えることに立脚している．この表現によれば，ごく一部の労働者には基準濃度以下でも健康影響が実際起きるかもしれないという事が考えられる．すべてのばく露は，合理的に可能な限り基準濃度よりできるだけ小さくすべきであるということの理由の一つはここにある．作業場の気中濃度は本来変動があるため，全てのばく露が基準値以下であることを保証することはできない．しかし，基準値を超えるばく露の割合がある割合より小さいことを統計的に証明することは可能である．この考え方が，超過割合の検定の根拠である．超過割合の点推定値の不確実性は，その信頼区間の算出により数値化できる",{"$nulls":3},972,1029,1087,1081,1056,282,1175,917,894,973,417,1006,964,1097,403,0]
[null,"95% upper confidence limit on the exceedance fraction.  We have an estimate of the exceedance fraction (see above), but this estimate is uncertain, and we are 95% sure that the real exceedance fraction is smaller than the UCL95%.  The combination of LCL95% and UCL95% forms a 90% confidence interval around the exceedance fraction estimate",null,63,"comm.\nConcept","95% upper confidence limit on the exceedance fraction.  We have an estimate of the exceedance fraction (see above), but this estimate is uncertain, and we are 95% sure that the real exceedance fraction is smaller than the UCL95%.  The combination of LCL95% and UCL95% forms a 90% confidence interval around the exceedance fraction estimate","Límite superior de confianza de la fracción excedente: Tenemos una estimación del la fracción excendete (Ver arriba), que sabemos tiene incertidumbre, pero estamos seguros que 95% que la fraccion excedente real es menor que el LCS95%. La combinación de LCI95% y el LCS95%, conforma un intervalo de confianza de 90% alrededor de la fracción excedente estimada.","Limite supérieure de confiance à 95% sur la fraction de dépassement.  Nous avons un estimé de cette fraction, mais il est entouré d'incertitude, et nous sommes surs à 95% que la fraction réelle est inférieure à LCsup.1,95%.  La combinaison de LCinf.1,95% et LCsup.1,95% forme un intervalle de confiance à 90% autour de l'estimé de la fraction de dépassement.","Obere 95%-Konfidenzgrenze beim Überschreitungsanteil. Wir haben eine Schätzung des Überschreitungsanteils (siehe oben), aber diese Schätzung ist unsicher, und wir sind zu 95% sicher dass der richtige Überschreitungsanteil kleiner ist als die OKG95%. Die Vereinigung von der UKG95% und der OKG95% bilden einen 90%-Konfidenzintervall um die Schätzung des Überschreitungsanteils.      ","Limite superiore dell'intervallo di confidenza 95% della frazione eccedente. Il nostro stimatore della frazione eccedente é incerto, ma possiamo essere sicuri al 95% che la frazione eccedente effettiva sarà inferiore al Lcsuo.1.95%. La combinazione dei due limiti di confidenza LCinf 1.95% e LCsup 1.95% definisce un intervallo di confidenza del 90% intorno al valore stimato della frazione eccedente","超标比例95%可信区间上限。我们已经能够对超标比例进行估计（如上），但是该估计具有不确定性，而且我们只有95%的信心认为实际的超标比例是小于UCL95%的水平的。结合LCL95%和UCL95%，可以得到一个超标比例估计值的90%可信区间。","Limite superior de confiança 95% da fração excedente. Nós temos uma estimativa da fração excedente (ver acima), mas esta estimativa tem uma incerteza, e temos 95% de certeza de que a real fração excedente é menor do que o LCS 95%. A combinação do LCI95% e LCS 95% conforma um intervalo de confiança de 90% em torno da fração excedente estimada.","95% nad hladinou spolehlivosti zlomku překročení. Máme odhad pro zlomek překročení (viz nahoře) , ale tento odhad je nejistý a máme 95% jistotu, že reálný zlomek překročení je menší než UCL95%. Kombinace LCL95% a UCL95% formuje 90% jistotního intervalu okolo odhadu zlomku překoročení.","आधिक्य अंश पर 95% उच्चतर विश्वास सीमा. हमारे पास आधिक्य अंश का अनुमान होता है (देखें ऊपरी मद), परंतु यह अनुमान अनिश्चित है और हम 95% आश्वस्त होते हैं कि वास्तविक आधिक्य अंश युसीएल 95% से कम है. एलसीएल1, 95% तथा युसीएल1, 95% का संयोजन, 90% विश्वास अंतर सृजित करता है, जो करीब-करीब गाणितिक मध्य अनुमान होता है.","95% Bovenste BetrouwbaarheidsLimiet op de overschrijdingsfractie (OF). Er bestaat een schatting van de OF (zie hoger), maar deze schatting is onzeker, en we zijn 95% zeker dat de werkelijke OF kleiner is dan de BBL95%. De combinatie van OBL95% en BBL95% vormt een 90% betrouwbaarheidsinterval rondom de schatting van de OF","95% 신뢰상한 초과율. 초과율 (위 참조)의 추정치가 있지만,이 추정치는 불확실하며, 실제 초과율이 신뢰상한95 %보다 작다는 것을 95% 확신합니다. 신뢰하한95%와 신뢰상한95%의 조합은 초과율 추정 부근의 90% 신뢰 구간을 형성합니다.","95% øvre konfidensgrense til overskridelsesfraksjonen. Vi har et estimat av overskridelsesfraksjon (se ovenfor), men dette anslag er usikkert, og er vi 95% sikker på at den virkelige overskridelses fraksjonen er mindre enn den ØKG95%. Kombinasjonen av NKG95% og ØKG95% danner et 90% konfidensintervall rundt den estimerte overskridelsesfraksjonen.","Aşım fraksiyonu üzerinde% 95 üst güven sınırı. Aşım fraksiyonu için tahminde bulunuyoruz (yukarıya bakınız), fakat bu tahmin belirsizdir ve %95 eminiz ki gerçek aşılma fraksiyonu %95 UCL'den küçüktür. %95 LCL ve %95 UCL kombinasyonu tahmini aşılma kısmını etrafında % 90 güven aralığı oluşturur.","95% верхний доверительный предел  фракции превышения. Существует расчет  фракции превышения (см. выше), но этот расчет является не точным, и мы на 95% уверены, что реальная доля превышений меньше 95% ВДП. Сочетание НДП 95% и ВДП 95% образует 90% доверительного интервала около расчитанной фракции превышения.","超過割合の片側95%信頼区間の上限値．超過割合の推定値を得た場合（上欄），その推定値には不確実性が伴うが，ここでは真の超過割合がUCL95%より小さいことが95%の信頼性をもって言える．LCL95%とUCL95%は超過割合の推定値の上下90%の信頼区間を形成する．",{"$nulls":3},339,359,358,382,400,119,344,285,308,322,136,347,295,308,132,0]
[null,0,null,64,"comm.\nConcept",{"$nulls":18},0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
[null,"The arithmetic mean of the exposure profile based\non normal parametric statistic. However ,except in the case of noise measurements expressed in dB, occupational exposure profiles are generally not normally distributed but rather lognormally distributed.",null,65,"comm.\nConcept","The arithmetic mean of the exposure profile based\non normal parametric statistic. However ,except in the case of noise measurements expressed in dB, occupational exposure profiles are generally not normally distributed but rather lognormally distributed.","La media aritmética del perfil de exposición basado en estadística paramétrica normal. Sin embargo, excepto los niveles de ruido expresados en dB, los perfiles de exposición ocupacional tiene una distribución logarítmica, en lugar de una distibución normal. ","La moyenne arithmétique du profil d'exposition basée sur une distribution normale. À noter que, excepté dans le cas de mesures de bruit exprimées en dB, les données d'exposition en milieu de travail sont distribuées conformément à un profil log-normal plutôt que normal.","Der arithmetische Mittelwert des Expositionsprofils auf Grund der Parameterstatistiken für die logarithmische Normalverteilung. Dennoch, abgesehen von Lärmmessungen die in dB ausgedrückt sind, sind Expositionsprofile auf dem Arbeitsplatz hauptsächlich nicht normal verteilt sondern eher lognormal verteilt.","La media aritmetica del profilo d'esposizione basata su una distribuzione normale. Da notare che, a parte le misure del rumore espresse in dB, i valori d'esposizione nell'ambiente di lavoro presentano piuttosto una distribuzione log-normale.","接触资料的算术均数来自于正态的参数统计。但是，除了以dB表示的噪音测量数据之外，职业接触资料普遍都不是正态分布的，而更常见的是对数正态分布。","A média aritmética do perfil de exposição é baseado na estatística paramétrica normal. No entanto, exceto no caso das medições de ruído expressas em dB, os perfis de exposição ocupacional geralmente não têm uma distribuição normal, mas sim uma distribuição lognormal.","Aritmetický průměr expozičního profilu popisuje data za předpokladu normálního rozdělení. Nicméně, kromě případu měření hluku vyjádřeného v dB, jsou pracovní expoziční profily rozděleny spíše logaritmicko-normálně.","नोर्मल प्राचलिक सांख्यिकी के आधार पर एक्स्पोजर प्रोफाइल का गाणितिक मध्य. हालांकि, डेसिबल में व्यक्त ध्वनि नाप के मामले के सिवा, व्यावसायिक एक्स्पोजर प्रोफाइल, सामान्यत: नोर्मल रूप से वितरित नहीं होते हैं परंतु लोग नोर्मल रूप से वितरित होते हैं.","Het rekenkundig gemiddelde van het blootstellingsprofiel gebaseerd op de parametrische statistieken van de normaalverdeling. Blootstellingsprofielen zijn (behalve in het geval van geluidsmetingen uitgedrukt in dB) echter meestal niet normaal maar eerder lognormaal verdeeld.","정규 모수적 통계에 기반된 노출 개요서의 산술 평균. 그러나, dB로 명시된 소음측정인 경우를 제외하고, 일반적으로 직업 노출 개요서는 정규 분포가 아닌 로그정규 분포를 나타냅니다.","Det aritmetiske gjennomsnittet av eksponeringsprofilen er basert på normal parametrisk statistikk. Imidlertid, bortsett fra i tilfellet av lydmålinger uttrykt i dB, er yrkesmessig eksponeringsprofiler generelt ikke normalfordelt, men snarere log-normalfordelt.","Maruziyet profilinin aritmetik ortalaması normal parametrik istatistiğe dayanmaktadır. Ancak, dB cinsinden ifade edilen gürültü ölçümleri dışında, mesleki maruziyet profilleri genellikle normal dağılım göstermemekte aksine lognormal dağılımdadır. ","Среднее арифметическое профиля воздействия вещества основанно на нормальной параметрической статистике. Тем не менее, за исключением случая измерений шума измеряемого в децибелах, профиль профессионального воздействия вещества, как правило распределяется логнормально.","正規分布に基づくばく露分布の算術平均値．但し，dBで表される騒音測定値の場合を除き，職業性のばく露分布は一般に正規分布でなく対数正規分布する．",{"$nulls":3},254,258,270,306,241,70,267,214,244,274,101,260,247,268,71,0]
[null,"The artihmetic mean one sided 95%\nlower confidence limit ",null,66,"comm.\nConcept","The artihmetic mean one sided 95%\nlower confidence limit ","El límite de confianza inferior de la media aritmética de unilateral LCI1,95%","La limite inférieure de confiance unilatérale à 95% sur la moyenne arithmétique.","Der arithmetische Mittelwert mit einseitiger unteren 95%-Konfidenzgrenze.","Il limite inferiore dell'intervallo di confidenza unilaterale 95% per la media aritmetica","算术均数的单侧95%可信限下限","Limite inferior de confiança unilateral 95% da média aritimética.","Jenostranná 95% hladina spolehlivosti pro aritmetický průměr ","गाणितिक मध्य एकतरफा 95% न्यून विश्वास सीमा","De eenzijdige Onderste 95% BetrouwbaarheidsLimiet op het rekenkudig gemiddelde (OBL1,95%)","산술평균 단측 95% 신뢰하한.","Ensidig nedre 95% konfidensgrense til det aritmetiskgjennomsnitte.","Tek taraflı aritmetik ortalama %95 düşük güven sınırı"," Среднее арифметическое односторонне  низкому доверительному пределу 95%","算術平均値の片側95%信頼区間の下限値．",{"$nulls":3},57,77,80,73,89,15,65,61,42,89,17,66,53,72,20,0]
[null,"The arithmetic mean one sided  95% upper confidence limit. The combination of LCL1,95% and UCL1,95% forms a 90% confidence interval around the AM estimate  ",null,67,"comm.\nConcept","The arithmetic mean one sided  95% upper confidence limit. The combination of LCL1,95% and UCL1,95% forms a 90% confidence interval around the AM estimate  ","Límite superior unilateral de confianza de 95% de la media aritmética. La combinación de los límites de confianza unilaterales superiores o inferiores de 95% forman un intervalo de confianza de 90% alrededor de la estimación de la media aritmética.  ","La limite supérieure de confiance unilatérale à 95% sur la moyenne arithmétique. La combinaison des limites de confiances unilatérales à 95% inférieures et supérieures forme un intervalle de confiance à 90% autour de l'estimé de la moyenne arithmétique.","Der arithmetische Mittelwert mit einseitiger oberen 95%-Konfidenzgrenze. Die Vereinigung von der UKG1,95% und der OKG1,95% bilden einen 90%-Konfidenzintervall um den geschätzten arithmetischen Mittelwert.","Il limite superiore dell'intervallo di confidenza unilaterale 95% per la media aritmetica.  La combinazione dei due limiti di confidenza inferiore e superiore definisce un intervallo di confidenza del 90% intorno al valore stimato della media aritmetica.","算术均数的单侧95%可信限上限。结合LCL1，95%和UCL1，95%，可得到AM估计值的90%可信区间。","Limite de confiança superior unilateral 95% da média aritmética. A combinação de LCI 1,95% e LCS 1,95% define um intervalo de confiança de 90% ao redor MA estimada.","Jenostranná 95% hladina spolehlivosti pro aritmetický průměr.  Kombinace LCL1,95% and UCL1, 95% tvoří 90% interval spolehlivosti pro odhad AP. ","गाणितिक मध्य एकतरफा 95% न्यून विश्वास सीमा. एलसीएल1, 95% तथा युसीएल1, 95% का संयोजन, 90% विश्वास अंतर सृजित करता है जो करीब-करीब गाणितिक मध्य अनुमान होता है.","De eenzijdige Bovenste 95% BetrouwbaarheidsLimiet op het rekenkudig gemiddelde (BBL1,95%). De combinatie van OBL1,95% en BBL1,95% vormt een 90% BI rondom de schatting van het RG.","산술평균 단측 95% 신뢰상한. 신뢰하한1, 95%와 신뢰상한1, 95%의 조합은 산술평균 추정 부근의 90% 신뢰 구간을 형성합니다.","Ensidig øvre 95% konfidensgrense til aritmetisk gjennomsnitt (AG). Kombinasjonen av NKG1, 95% og ØKG1, 95% danner et 90% konfidensintervall rundt estimatet av AG. ","Tek taraflı aritmetik ortalama %95 yüksek güven sınırı. %95 LCL1 ve %95 UCL1 kombinasyonu tahmini aritmetik ortalama etrafında % 90 güven aralığı oluşturur."," Среднее арифметическое односторонне верхнему доверительному пределу 95%. Сочетание НДП 1,95% и  ВДП 1,95% образуют 90% доверительный интервал около расчитанного СА.","算術平均値の片側95%信頼区間の上限値．\nLCL1,95%とUCL1,95%は算術平均値の上下90%の信頼区間を形成する．",{"$nulls":3},156,250,253,204,254,53,164,143,157,178,75,163,156,165,61,0]
[null,"Estimate of the 95th percentile of the exposure profile. See definition in the lognormal parameters section.",null,68,"comm.\nConcept","Estimate of the 95th percentile of the exposure profile. See definition in the lognormal parameters section.","Estimación del percentil 95 del perfil de exposición. Ver la definición en la sección de los parametros de la distribuión logarítmica.  ","Estimé du 95e percentile du profil d'exposition. Voir définition dans la section des paramètres de la distribution log-normale.","Die 95. Perzentile Schätzung des Expositionsprofils. Siehe Definition im Abschnitt über den lognormalen Parametern.","Stimatore del 95simo percentile del profilo d'esposizione. Vedi definizione nella sezione Parametri statistici per la distribuzione log-normale","接触资料的第95百分位数估计。请见对数正态参数部分中的定义。","Estimativa do percentil 95 do perfil de exposição. Ver definição na seção parâmetros lognormais.","Odhad 95. percentilu expozičního profilu. Viz definice v sekci logaritmicko-normálních parametrů. ","एक्स्पोजर प्रोफाइल के 95% प्रतिशत का अनुमान. परिभाषा हेतु लोगनोर्मल मानदंड का खंड देखें.","Schatting van het 95ste Percentiel van het blootstellingsprofiel. Zie definitie in de de sectie lognormale parameters.","노출 개요서의 95번째 백분율 추정치. 로그 정규 모수 섹션에서 정의를 참조하십시오.","Estimat av 95 persentilen av eksponeringensprofilen. Se definisjon i delen om lognormal parametre.","Maruziyet profilinin 95. yüzdelik dilimi tahmin etme. Lognormal parametreler bölümündeki açıklamaya bakınız. ","Оценка 95-го перцентраля профиля воздействия. См. определение в секции логнормальные параметры.","ばく露分布の95パーセンタイル値の推定値．定義は対数正規分布の項を見よ．",{"$nulls":3},108,136,127,115,143,30,96,98,88,118,47,98,109,95,36,0]
[null,"95% upper tolerance limit on the estimate of the 95th percentile.See definition in the lognormal parameters section",null,69,"comm.\nConcept","95% upper tolerance limit on the estimate of the 95th percentile.See definition in the lognormal parameters section","Lìmite de Tolerancia Superior a 95% del percentil 95. Ver la definición en la sección de los parametros de la distribuión logarítmica.","Limite de tolérance à 95% sur le 95e percentile. Voir définition dans la section des paramètres de la distribution log-normale.","Obere 95%-Konfidenzgrenze für die Schätzung des 95. Perzentiles. Siehe Definition im Abschnitt über den lognormalen Parametern. ","Limite  dell'intervallo di tolleranza. Vedi definizione nella sezione Parametri statistici per la distribuzione log-normale","第95百分位数估计值的95%容许限值上限。请见对数正态参数部分中的定义。","Limite de tolerância superior de 95% na estimativa  do percentil 95. Ver definição na seção de parâmetros lognormais.","95% horní toleranční limit odhadu 95. percentilu. Viz definice v sekci logaritmicko-normálních parametrů.","95% प्रतिशत के अनुमान पर 95% उच्चतर सह्यता सीमा. परिभाषा हेतु लोगनोर्मल मानदंड का खंड देखें.","95% Bovenste Tolerantie Limiet op de schatting van het 95ste Percentiel. Zie definitie in de de sectie lognormale parameters.","95번째 백분율의 추정치에 대한 95% 상위 허용 한계. 로그 정규 모수 섹션에서 정의를 참조하십시오.","95% øvre toleransegrense til estimat av 95 persentilen. Se definisjonen i delen om lognormalparametre.","%95'lik yüzdelik dilimin tahmininde %95 yüksek tolerans limiti. Lognormal parametreler bölümündeki açıklamaya bakınız. ","95%  верхней допустимый предел на расчетный 95й процентиль. См. определение в секции логнормальные параметры.","95パーセンタイル値の推定値の95%上側許容区間．定義は対数正規分布の項を見よ．",{"$nulls":3},115,134,127,128,123,36,117,105,92,125,57,102,119,109,40,0]
[null,"Exceedance Fraction; it is the proportion of the exposure\nprofile that exceeds the OEL. See definition in the lognormal parameters section ",null,70,"comm.\nConcept","Exceedance Fraction; it is the proportion of the exposure\nprofile that exceeds the OEL. See definition in the lognormal parameters section ","Fracción Excendente: es la porporción del perfil de esxposición que excede el LEO. Ver la definición en la sección de los parametros de la distribuión logarítmica.","Fraction de dépassement; c'est la proportion des valeurs du profil d'exposition qui dépassent la VLE. Voir définition dans la section des paramètres de la distribution log-normale.","Überschreitungsanteil: es ist der Anteil des Expositionsprofils der die MAK überschreitet. Siehe Definition im Abschnitt über den lognormalen Parametern. ","Frazione eccedente: rappresenta la percentuale dei valori di un profilo superiori al valore limite di soglia (TLV). Vedi definizione nella sezione Parametri statistici per la distribuzione log-normale","超标比例；这是接触监测数据中超过OEL水平的部分。请见对数正态参数部分。","Fração Excedente; é a porção do perfil de exposição que ultrapassa o LEO. Ver definição na seção de parâmetros lognormais.","Zlomek překročení; část expozičního profilu, která překračuje EL. Viz definice v sekci logaritmicko-normálních parametrů.","आधिक्य अंश,एक्स्पोजर प्रोफाइल का वह हिस्सा है जो ओइएल से अधिक हो. उसकी परिभाषा हेतु लोगनोर्मल मानदंड का खंड देखें.","Overschrijdingsfractie; de fractie van het blootstellingsprofiel die de GBB overschrijdt. Zie definitie in de de sectie lognormale parameters.","초과율; 직업노출기준을 초과하는 노출 개요서의 비율입니다. 로그 정규 모수 섹션에서 정의를 참조하십시오.","Overskridelse fraksjon; det er andelen av eksponeringensprofil som overstiger faregrensen. Se definisjon i delen om lognormalparametre.","Aşım Kesri (Fraksiyonu); OEL'tin aşılması durumlarında üst miktrar üzerindeki maruz kalma kesiridir. Tanımlarda lognormal parametreler kısmına bakınız.","Фракция превышения- это пропорция профиля воздействия, которая превышает  ЛПО. См. определение в секции логнормальные параметры.","超過割合ともいう．ばく露分布のうちばく露限界値を超えているものの割合．定義は対数正規分布の項を見よ．",{"$nulls":3},139,163,180,154,200,36,122,121,114,142,58,135,151,128,50,0]
[null,"Exposure Profile: Magnitude and variability of exposures for a\nSimilar Exposure Group (SEG). This include some understanding of of the Central Tendency of the exposures (such as the mean\nexposure) and some understanding of the breadth, or variability,\nof the exposures (such as the range of exposures). The exposure profile can be represented by a statistical distribution, usually the lognormal distribution in the case of occupational exposures",null,71,"comm.\nConcept","Exposure Profile: Magnitude and variability of exposures for a\nSimilar Exposure Group (SEG). This include some understanding of of the Central Tendency of the exposures (such as the mean\nexposure) and some understanding of the breadth, or variability,\nof the exposures (such as the range of exposures). The exposure profile can be represented by a statistical distribution, usually the lognormal distribution in the case of occupational exposures","Perfil de exposición: es la magnitud y variabilidad de exposiciones para un Grupo de Exposición Similar (GES). Esto incluye el entendimiento de las tendencias centrales de exposición (tal como la exposición media), y algún entendimiento sobre la amplitud o variabilidad de las exposiciones (tal como el rango de exposición). El perfil de esposición puede ser representado por una distribución estadística, usualmente la distribución log-normal en el caso de las exposiciones ocupacionales. ","Profil d'exposition : ampleur et variabilité des expositions pour un groupe d'exposition similaire (GES). Cela inclut la connaissance de la tendance centrale des expositions (telle que la valeur d'exposition moyenne) et de la gamme ou variabilité des expositions (telle que l'étendue des expositions). Le profil d'exposition peut être représenté par une distribution statistique, généralement la distribution lognormale dans le cas des mesures d'exposition professionnelle.","Expositionsprofil: Ausmass und Variabilität von Expositionen für eine gleichartige Expositionsgruppe. Dies bezieht ein gewisses Verstehen von einer Mitteltendenz der Expositionen (so wie die Durchschnittsexposition) und von der Weite, oder der Variabilität, der Expositionen (so wie den Bereich der Expositionen) ein. Der Expositionsprofil kann mit einer statistischer Verteilung dargestellt werden, üblicherweise mit der logarithmischen Normalverteilung im Fall der Expositionen am Arbeitsplatz.","Profilo d'esposizione: intensità e variabilità dell'esposizione per un gruppo omogeneo d'esposizione (G.O.E.). Questo comprende l'informazione sulla tendenza centrale dell'esposizione (come il valore medio d'esposizione) e sulla variabilità  dell'esposizione (come il range dell'esposizione). Il profilo d'esposizione puo' essere rappresentato da una distribuzione statistica, e generalmente, nel caso dell'esposizione in ambiente professionnale, da una distribuzione log-normale.","接触资料：相似接触组（SEG）的接触强度和变异性。其中包括了一些关于接触的集中趋势（如平均接触水平）和接触的宽度，或者变异度（如接触浓度范围）的内容。接触浓度资料可以通过一个统计学分布进行重现，在职业卫生中通常是对数正态分布。","Perfil de Exposição: Magnitude e variabilidade da exposição de um Grupo de Exposição Similar (GES). Isto inclui algum entendimento sobre Tendências Centrais de Exposição (tais como exposição média) e alguma compreensão da amplitude, ou variabilidade das exposições (tais como faixas de exposições). O perfil de exposição pode ser representado por uma distribuição estatística, normalmente uma distribuição lognormal no caso de exposições ocupacionais.","Expoziční profil: Význam a variabilita expozic pro Podobné Expoziční Skupiny (PES). Expoziční profil zahrnuje centrální charakteristiku expozic (průměrná expozice) a rozsah nebo variabilitu expozic (rozmezí expozic). Expoziční profil může být reprezentován statistickou distribucí, obvykle logaritmicko-normální distribucí v případě pracovních expozic.","एक्स्पोजर प्रोफाइल : समान एक्स्पोजर समूह (एसइजी) के लिए एक्स्पोजरों की महत्ता एवं चलनीयता. इसमें एक्स्पोजरों (जैसे कि मध्य एक्स्पोजर) के केन्द्रीय झुकाव की कुछ समझ सम्मिलित है तथा एक्स्पोजरों (जैसे कि एक्स्पोजरों का सीमाक्षेत्र) की चौडाई या चलनीयता की समझ सम्मिलित है. एक्स्पोजर प्रोफाइल, सांख्यिकीय वितरण द्वारा प्रस्तुत किया जा सकता है, सामान्यत: व्यावसायिक एक्स्पोजरों के मामले में लोग नोर्मल विरतण द्वारा.","Blootstellingsprofiel: Grootteorde en variabiliteit van blootstellingen van een Homogene BlootstellingsGroep (HBG). Dit omvat enig begrip van centraliteits- (zoals de gemiddelde blootstelling) en spreidingsmaten (zoals het blootstellingsbereik). Het blootstellingsprofiel kan voorgesteld worden door een statistische verdeling, gewoonlijk de lognormale verdeling in het geval van beroepsmatige blootstellingen.","노출 개요서: 유사노출그룹 (SEG)의 노출의 크기폭과 변이성. 노출의 중심 경향성(예 : 평균 노출)과 노출의 폭이나 변이성 (예 : 노출 범위 등)의 일부 개념을 포함합니다. 노출 개요서는 통계 분포, 직업적 노출의 경우 일반적으로 로그 정규 분포로 표현 할 수 있습니다.","Eksponerings Profil: Høyest nivå og variasjon av eksponeringer for en sammenlignbart eksponert gruppe (SEG). Dette gir en viss oversikt over sentral mål på eksponeringene (slik som gjennomsnittlig eksponering) og en viss forståelse av bredden, eller variasjon, av eksponeringene (for eksempel tidsserien av eksponeringer). Eksponeringsprofilen kan representeres ved en statistisk fordeling, vanligvis lognormal distribusjon i tilfelle av yrkesmessig eksponering.","Maruziyet Profili: Benzer Maruziyet Grubu (SEG) için maruziyetin boyutu ve değişkenliği. Bu, maruziyetin Merkezi Eğilimin (ortalama maruziyet gibi) anlaşılmasını ve maruziyetin uzaklığını veya değişkenliğinin (maruziyet aralığı gibi) anlaşılmasını içermektedir. Maruziyet profili istatistiksel dağılımla ifade edilebilir, genellikle mesleki maruziyet durumunda lognormal dağılım kullanılır.","Профиль воздействия вещества: величина и изменение воздействия для Группы подобного воздействия. Это включает понятия Центральной Тенденции воздействия (например среднее арифметическое), широты или изменчивости воздействия ( диапазон  воздействия). Профиль воздействия вещества может быть представлен статистическим распределением, как правило, логнормальным в случае профессионального облучения.","ばく露分布．ある同等ばく露グループ（SEG）のばく露の大きさとバラツキを示す．ばく露の代表値（平均値等）や広がり（またはバラツキ．ばく露の範囲など）が含まれる．職業性ばく露の場合，ばく露分布は通常対数正規分布として統計的に表される．",{"$nulls":3},446,490,473,496,480,113,451,352,409,410,154,462,390,396,116,0]
[null,"This file was originaly created by John Mulhausen and then\nmodified in its multilingual version by Daniel Drolet et al.",null,72,"INTRO","This file was originaly created by John Mulhausen and then\nmodified in its multilingual version by Daniel Drolet et al.","Este archivo fue creado originalmente por John Mulhausen y luego\nmodificado a su versión multilíngüe por Daniel Drolet et al.","Ce fichier a été créé à l'origine par John Mulhausen (3M) et ensuite modifié\ndans la présente version multilingue par Daniel Drolet et al.","Die Datei wurde ursprünglich von John Mulhausen entworfen und anschliessend\nvon Daniel Drolet in seine mehrsprachige Fassung bearbeitet. ","Questo file é stato creato inizialmente da John Mulhausen (3M) e in seguito modificato,\nper l'attuale versione multilingua, da Daniel Drolet.","该软件首先由John Mulhausen创立，经Daniel Drolet等人的修改后成为多国语言版本。","Este arquivo foi originalmente criado por John Mulhausen e modificado\nem sua versão multilingüe por Daniel Drolet et al.","Tento dokument vytvořil John Mulhause. Dokument modifikoval\ndo jazykových verzí tým autorů, vedený Danielem Droletem.","यह फाइल मूल रूप से जोन मुलहसन द्वारा सृजित की गई है और तद्पश्चात्\nउनके बहुभाषी संस्करण के लिए डेनियल ड्रोलेट द्वारा संशोधित की गई है.","Dit bestand is oorspronkelijk opgesteld door John Mulhausen\nen later gewijzigd in zijn meertalige versie door Daniel Drolet et al.","이 파일은 처음으로 John Mulhausen이 만든 후 Daniel Drolet 등에 의하여 다국어 버전으로 바뀌었습니다.","Dette verktøyet ble opprinnelig laget av John Mülhausen og deretter\nmodifisert i en flerspråklig versjonen av Daniel Drolet et al. ","Bu dosya John Mulhausen tarafından oluşturulmuş olup daha\nsonrasında çokdilli versiyonları Daniel Drolet tarafından düzenlenmiştir.","Этот документ был разработан Джоном Мюлхасеном\n и затем изменен в многоязычной версии Данэлем Дроле и другими.","このツールはJohn Mulhausenによりオリジナルが作成され，Daniel Droletらにより多言語版とされた．",{"$nulls":3},119,125,138,137,141,52,120,117,133,130,69,131,131,110,60,0]
[null,"est. AM",null,73,"Graph","est. AM","MA est","MA est.","est. AM ","MA est.","est. AM","MA est.","odh. AP","अनुमानित गाणितिक मध्य","RG ges.","추정 산술 평균","est AG","tahmini AO = Aritmetik Ortalama ","расчитанное СА","算術平均値の推定値",{"$nulls":3},7,6,7,8,7,7,7,7,21,7,8,6,32,14,9,0]
[null,"LCL",null,74,"Graph","LCL","LIC","LC inf.","UKG","LC inf.","LCL","LCI","LCL","एलसीएल","OBL","신뢰하한","NKG","LCL","НДП","LCL",{"$nulls":3},3,3,7,3,7,3,3,3,6,3,4,3,3,3,3,0]
[null,"UCL",null,75,"Graph","UCL","LSC","LC sup.","OKG","LC sup.","UCL","LCS","UCL","युसीएल","BBL","신뢰상한","ØKG","UCL","ВДП","UCL",{"$nulls":3},3,3,7,3,7,3,3,3,6,3,4,3,3,3,3,0]
[null,"Example",null,76,"comm.\nExemple","Example","Ejemplo","Exemple","Beispiel","Esempio","举例","Exemplo","Příklad","उदाहरण","Voorbeeld","예시","Eksempel","Örnek ","Пример","例",{"$nulls":3},7,7,7,8,7,2,7,7,6,9,2,8,6,6,1,0]
[null,"The Occupational Exposure Limit, an upper limit chosen to provide adequate protection of workers' health and safety; normally the TLV (PEL or VLE) is used for this limit. ",null,77,"comm.\nExemple","The Occupational Exposure Limit, an upper limit chosen to provide adequate protection of workers' health and safety; normally the TLV (PEL or VLE) is used for this limit. ","Limite de Exposicion Ocupacional LEO, un limite superior seleccionado para proveer la adecuada proteccion a la salud y seguridad de los trabajadores; el VLP (PEL o VLE) se usa normalmente como este limite. ","La valeur limite d'exposition, est une limite supérieure permettant une protection adéquate pour la santé et la sécurité du travailleur ; la TLV ou une VLE est normalement utilisée pour cette limite.","Die maximale Arbeitskonzentration, eine obere Grenze, die für einen passenden Schutz für die Gesundheit und die Sicherheit der Arbeiter festgelegt wird; das MAK-Wert wird in der Regel für diese Grenze benutzt.","Il valore limite di soglia d'esposizione rappresenta un limite superiore ceh permette una protezione adeguata per la salute e la sicurezza dei lavoratori; si fa generalmente riferimento alla TLV","职业接触限值，是一个上限浓度，目的是为工人的健康和安全提供充分的保护；一般使用TLV（PEL或者VLE）作为该上限值。","O Limite de Exposição Ocupacional, um limite máximo escolhido para proporcionar uma proteção adequada à saúde e segurança dos trabalhadores; normalmente o TLV (PEL ou VLE) é usado como este limite.","Limit pracovní expozice, horní limit vybraný k poskytování adekvátní ochrany zdraví pracovníků a jejich bezpečí; normálně je pro tento limit používána zkratka EL (PEL nebo NPK-P).","व्यावसायिक एक्स्पोजर सीमा, कामगारों के स्वास्थ्य एवं सुरक्षा के लिए पर्याप्त संरक्षण प्रदान करने हेतु पसंद की गई ऊपरी सीमा, सामान्यत: इस सीमा के लिए टीएलवी (पीइएल या वीएलइ) का उपयोग किया जाता है.","De Grenswaarde voor Beroepsmatige Blootstelling, een bovenste limiet gekozen om adequate bescherming van gezondheid en veiligheid van werknemers te bieden; meestal wordt de GBB (Belgische GBB) gebruikt voor deze limiet.","직업노출기준, 근로자 건강과 안전의 적절한 보호를 제공하기 위해 선택한 상한; 일반적으로 TLV (PEL) 가 사용됩니다.","Tiltaks- eller grenseverdi (YGV), en øvre grense valgt å gi tilstrekkelig vern av arbeidstakeres helse og sikkerhet. Andre grenseverdier f.eks. TLV, MAK, WEL, WEEL finnes også.","Mesleki Maruziyet Limiti, çalışanın sağlığını ve güvenliğini yeterli derecede korumak için seçilen üst limit; genellikle bu limit için TLV (PEL veya VLE) kullanılır. ","ЛПО - это предельная концентрация,  при которой  обеспечена адекватная защита здоровья рабочего. Обычно  ПДК использованы как ЛПО.","ばく露限界値．労働者の健康と安全が十分保障されるように設定された上限値．通常はTLV（またはPEL, VLE）が用いられる．",{"$nulls":3},171,206,199,209,194,59,197,179,195,219,68,176,166,130,62,0]
[null,"With a GSD value of 2.1, the action level should be set at 0,1 times 0,15 µg/m³ equal to 0,015 µg/m³  (Leidel, 1976)",null,78,"comm.\nExemple","With a GSD value of 2.1, the action level should be set at 0,1 times 0,15 µg/m³ equal to 0,015 µg/m³  (Leidel, 1976)","Con una DEG de 2,1, el nivel de acción debe ser fijado en 0,1 x 0,15 µg/m³, igual que 0,015 µg/m³ (Leidel, 1976)","Avec un ETG de 2,1, le niveau d'intervention devrait être fixé à 0,1 x 0,15 µg/m³, ce qui donne 0,015 µg/m³ (Leidel, 1976)","Mit einer GSD gleich 2.1 sollte der Wirkungspegel auf 0,1 mal 0,15 µg/m³ gleich 0,015 µg/m³ festgelegt werden (Leidel, 1976).","Con una deviazione standard geometrica di 2.1, il limite d'accettazione (action level) dovrebbere essere fissato a 0,1 x 0,15 µg/m³ = 0,015 µg/m³ (Leidel, 1976)","当GSD值为2.1时，控制水平必须被设定为0.15 µg/m³ 的0.1倍，即0.015 µg/m³ （Leidel，1976）","Com um DPG de 2,1, o nível de ação deve ser fixado em 0,1 vezes 0,15 μ g / m³, igual a 0,015 μ g / m³ (Leidel, 1976)","S hodnotou GDS 2.1 by hladina působení měla být nastavena na 0,1x 0,15 µg/m³ rovno 0,015 µg/m³  (Leidel, 1976)","जीएसडी मूल्य 2.1 के साथ, कार्य स्तर को 0, 1 समय, 0,15 µg/m³ = 0,015 µg/m³  (लैडेल, 1976) पर सेट करना चाहिए.","Met een GSA waarde van 2,1 moet de Actiewaarde ingesteld worden op 0,1 keer 0,15 µg/m³ of 0,015 µg/m³ (Leidel, 1976)","2.1 기하표준편차로 감시기준이 0.1 곱하기 0.15 µg/m³ 인 0.015 µg/m³ 로 설정되어야합니다 (Leidel, 1976) ","Med et GSA på 2,1, bør \"Tiltaksnivået\" settes til 0,1 ganger 0,15 mg/m³ lik 0,015 mg/m³ (Leidel, 1976).","2.1'lik GSD değeri ile, aksiyon seviyesi 0.1*0.15 µg/m³ = 0,015 µg/m³  olarak set edilmelidir. (Leidel, 1976)","Если ГСО =2,1 тогда Пороговая Доза должна быть  0,1 х 0,15 мг/м3 и равна 0,015мг/м3 (Лейдел, 1976)","幾何標準偏差が2.1の時，アクションレベルは0,15 µg/m³の10%，即ち0,015 µg/m³とすべきである．  (Leidel, 1976)",{"$nulls":3},116,112,122,125,160,64,116,110,107,116,77,103,109,98,74,0]
[null,"est. AM = arithmetic mean (0.074) of a lognormal distribution calculated by the Minimum Variance Unbiased Estimate (MVUE). The arithmetic mean is the correct parameter for evaluating cumulative exposure.",null,79,"comm.\nExemple","est. AM = arithmetic mean (0.074) of a lognormal distribution calculated by the Minimum Variance Unbiased Estimate (MVUE). The arithmetic mean is the correct parameter for evaluating cumulative exposure.","MA est. = media aritmética (0,074) de una distribución log-normal calculada por el método de la varianza mínima estimada no sesgada (MVUE). La MA es el parámetro correcto para evaluar exposición acumulada. ","MA est. = moyenne arithmétique (0,074) d'une distribution log-normale calculée par la méthode de Land. Cette moyenne arithmétique est le bon paramètre pour évaluer une exposition cumulée.","est. AM = arithmetischer Mittelwert (0,074) einer logarithmischen Normalverteilung berechnet mit Hilfe des erwartungstreuen Schätzer mit kleinster Varianz (MVUE). Das arithmetische Mittelwert ist der entsprechende Parameter zur Beurteilung der kumulierten Expositionen. ","MA est. = media aritmetica (0.074) di una distribuzione log-normale calcolata con il metodo di Land. Questo tipo di media aritmetica rappresenta un buon parametro per la valutazione di un'esposizione cumulativa","est. AM = 通过最小方差无偏估计（MVUE）得到的一个对数分布的算术均数（0.074）。该算术均数能够正确估计累计接触水平。","MA Est. = média aritmética (0,074) de uma distribuição lognormal calculada pela Variância Mínima Estimada Imparcial (VMEI). A média aritmética é o parâmetro correto para se avaliar uma exposição cumulativa.","odh. AP = aritmetický průměr (0,074) logaritmicko-normální distribuce vypočtený z Minimum Variance Unbiased Estimate (MVUE). Aritmetický průměr je vhodný parametr pro hodnocení kumulativní expozice.","अनु. एएम = न्यूनतम विचलन अनबायास्ड अनुमान (एमवीयुइ) द्वारा गिने गये लोग नोर्मल वितरण का अनुमानित गाणितिक मध्य (0, 074). गाणितिक मध्य, संचित एक्स्पोजर के मूल्यांकन के लिए सही मानदंड है.","RG ges. = rekenkundig gemiddelde (0,074) van een lognormale verdeling berekend via de Minimum Varantie Onververvalste Schatter (MVOS). Het RG is de correcte parameter om cumulatieve blootstelling te evalueren.","추정된 산술 평균 = 최소분산 불평추정값(MVUE)으로 계산된 로그정규분포의 산술평균 (0.074). 산술 평균은 누적 노출을 평가하기위한 올바른 매개 변수입니다.","est AG = aritmetisk gjennomsnitt (0,074) av en lognormal distribusjon beregnet med \"Minimum varians forventningsrett estimat\" (MVUE). Det aritmetiske gjennomsnittet er riktig parameter for å vurdere kumulativ eksponering.","Minimum Varyans Tarafsız Hesaplama (MVUE) ile hesaplanan lognormal dağılım için Hesaplanan AO = Aritmetik Ortalama (0.074). Aritmetik ortalama kümülatif maruziyeti hesaplamak için doğru parametredir. ","расчетное СА= среднее арифметическое  (0,074)логнормальных данных распределения, расчитанных с помощью Минимальной Дисперсией Несмещенной Оценки (MVUE). Среднее арифметическое значение- это правильный параметр для оценки совокупного воздействия.","算術平均値の推定値．対数正規分布をもとに最小分散不偏推定（MVUE）によって推定された算術平均値(0.074)．算術平均値は長期の健康リスクの評価に適した変数である．",{"$nulls":3},203,206,187,270,210,66,206,198,184,209,91,221,200,245,83,0]
[null,"The arithmetic mean's one sided 95% upper confidence limit (UCL1,95%) is calculated (0.116) and found to be below the OEL, one would be at least 95% sure that the exposure profile's AM was below the OEL.",null,80,"comm.\nExemple","The arithmetic mean's one sided 95% upper confidence limit (UCL1,95%) is calculated (0.116) and found to be below the OEL, one would be at least 95% sure that the exposure profile's AM was below the OEL.","Si el límite superior de confianza unilateral en 95% (UCL1,95%) de la media aritmética es menor que el LEO, uno puede estar al menos 95 % seguro que el perfil de exposición es menor que el LEO.","La limite de confiance supérieure unilatérale à 95% de la moyenne arithmétique (LCs 1,95%) a été calculée (0,116) et est inférieure à la VLE; on est alors assuré au moins à 95 % que le profil d'exposition de la MA estimée est inférieur à la VLE.","Der arithmetische Mittelwert mit einseitiger oberen 95%-Konfidenzgrenze (OKG 1,95%) ist gerechnet (0,116) und findet sich unter dem MAK-Wert, man wäre wenigstens zu 95% sicher dass der AM des Expositionsprofils unter dem MAK-Wert liegte.","Il limite di confidenza superiore unilaterale 95% della media aritmetica (LCs 1,95%) calcolato (0.116) é inferiore alla TLV; siamo dunque certi almeno al 95% che il profilo d'esposizione della MA stimata é inferiore alla TLV","计算该算术均数的单侧95%可信限上限（UCL，1，95%）为0.116，并发现低于OEL水平。因此至少有95%的信心认为该接触资料的AM低于OEL水平。","O limite de confiança superior unilateral 95% (LCS 1,95%) da média aritmética é calculado (0,116) e está abaixo do LEO, com pelo menos, com 95% de certeza de que a MA do perfil de exposição esta abaixo do LEO.","Vypočítaná horní mez spolehlivosti odhadu aritmetického půměru (UCL1, 95%, 0,116) je menší než EL. S pravděpodobností 95% lze tvrdit, že AP je pod EL. ","गाणितिक मध्य की एकतरफा 95% उच्च विश्वास सीमा (युसीएल 1, 95%) की गणना (0,116) की जाती है और ओइएल से कम पाया जाता है तो कोई भी कम से कम 95% निश्चित हो सकता है कि एक्स्पोजर प्रोफाईल का गाणितिक मध्य ओइएल से नीचे था.","De eenzijdige Bovenste 95% BetrouwbaarheidsLimiet op het rekenkudig gemiddelde (BBL1,95%) is berekend (0,116) en ligt onder de GBB. We kunnen op zijn minst 95% zeker zijn dat het RG van het blootstellingsprofiel onder de GBB ligt.","산술평균의 단측 95% 신뢰상한 (UCL1, 95%)은 (0.116)으로 계산되었고, 직업노출기준 이하로 나타났습니다.  이는 노출 개요서의 산술평균이 직업노출기준 이하임을  최소한 95% 확신할 수 있습니다.","Ensidig 95% øvre konfidensgrense (ØKG1, 95%) til det aritmetisk gjennomsnitt er beregnes (0,116) og funnet å være under YGV, og man er dermed minst 95% sikker på at eksponerings profilens AG er under YGV.","Aritmetik ortalamanın tek taraflı %95 üst güvenirlik sınırı (UCL %1.95) hesaplanır  (0,116) ve OEL altında bir değer olduğu bulunur. Bu hesaplama yapılırken maruz kalma kesiti Aritmetik Ortalamasının ''OEL'' altında olduğundan %95 kesin olmak gerekir."," Среднее арифметическое одностороннее  95%ВДП (1,95%) посчитанно (0,116) и найдено существенно меньшим чем ЛПО. Следовательно, можно быть на 95% уверенным, что СА профиля воздействия вещества меньше ЛПО.","算術平均値の片側95%信頼区間の上限値（UCL1,95%）が求められ（0.116），これはばく露限界値より小さい．従って、ばく露分布の算術平均値がばく露限界値より小さいことが，少なくとも95%の信頼性で言える．",{"$nulls":3},203,193,245,237,224,76,209,151,211,230,117,204,251,203,105,0]
[null,"The 95th percentile (0.187) point estimate forming a \"picture\" of the exposure profile's upper tail is important when evaluating the health hazards of agents with acute health effects or when evaluating noncompliance associated with exceeding an OEL.",null,81,"comm.\nExemple","The 95th percentile (0.187) point estimate forming a \"picture\" of the exposure profile's upper tail is important when evaluating the health hazards of agents with acute health effects or when evaluating noncompliance associated with exceeding an OEL.","El valor estimado del percentil 95 (0,187) visibiliza los valores de exposición en una-cola del perfil. Es importante cuando se evalúan los efectos agudos causados por peligros, o al evaluar la no-conformidad asociada cuando se excede el LEO.","La valeur estimée du 95ile (0,187) est une \"représentation\" de la région supérieure du profil d'exposition et est importante lors de l'évaluation du risque associé à des agents ayant des effets aigus sur la santé ou lors de mesures de conformité à une VLE.","Die 95. Perzentile (0,187) Punktschätzung, die ein \"Bild\" des oberen Gebietes des Expositionsprofils bildet, ist äusserst wichtig bei der Risikobeurteilung von Wirkstoffen mit akuten Wirkungen für die Gesundheit oder bei der Risikoeinschätzung einer Nichtübereinstimmung der MAK. ","Il valore stimato del 95simo percentile (0.187), fornendoci un'immagine della regione superiore del profilo dell'esposizione, é particolarmente importante per la valutare il rischio correlato all'esposizione a sostanze aventi effetto acuto sulla salute o per stimare il rischio di non conformità rispetto al limite di soglia (TLV).","第95百分位点估计值（0.187）提供了一个接触资料的上尾的\"图形\"轮廓，而且当在评价具有急性健康效应的化学物质的健康危害或者评价超过OEL时的危险度时是非常重要的。","O ponto de percentil 95 estimado (0,187) nos fornecendo uma \"foto\" da cauda superior do perfil de exposição, é importante quando se avaliam os riscos à saúde pela exposição a agentes químicos com efeitos agudos a saúde ou quando se avaliam não-conformidades associadas a ultrapassagem de um LEO.","Odhad hodnoty 95. percentilu (0,187) poskytujícího \"obraz\" horního konce expozičního profilu je zvláště důležitý v případě hodnocení zdravotního rizika činitelů, majících akutní vliv na zdraví nebo při hodnocení rizik spojených s překročením EL.","एक्स्पोजर प्रोफाइल की ऊपरी सीमा का चित्रण करने वाले 95वें प्रतिशत पाइन्ट अनुमान (0, 187) महत्वपूर्ण है, जब एक्युट स्वास्थ्य प्रभाव वाले एजेन्टों के स्वास्थ्य जोखिमों का मूल्यांकन किया जाए या ओइएल से अधिक के साथ जुडे अननुपालन का मूल्यांकन किया जाए.","De puntschatting van het 95ste Percentiel (0,187) levert een beeld van de bovenste staart van het blootstellingsprofiel en is van bijzonder belang in het evalueren van de gevaren van agentia met acute gezondheidseffecten of het evalueren van niet-naleving geassocieerd met het overschrijden van de GBB.","노출 개요서의 상한꼬리에 \"그림\"을 만든 95번째 백분위 점 (0.187) 추정치는  급성건강영향을 미치는 건강 유해요소를 평가할때나 직업노출기준에 비준수 위험을 평가할때 중요합니다. ","Punkt estimatet til 95-persentilen (0,187) danner et \"bilde\" av eksponerings profilens øvre hale og er viktig når man skal vurdere de helsemessige farene av et kjemikalies akutte helseeffekter eller når en skal vurder en eksponering opp mot tiltaks- eller grenseverdier (YGV).","Etkenlerin / ajanların insan sağlığına olan tehlikelerini değerlendirilmesinde veya OEL miktarının aşılması durumlarındaki uygunsuzlukların değerlendirilmesinde;  95'nci yüzdenin nokta hesabı önemlidir ve mazur kalma kesitinin üst kuyruğu ''tablo''sunun oluşturulamsında kullanılır.","95-й процентиль (0,187) дает предварительную оценку верхней границы профиля воздействия вещества. Этот аспект важен при оценке опасности при воздействии вещества с острым последствиям для здоровья или при оценке несоблюдения требываний связанных с превышением ПДК.","ばく露分布の上端を「象徴」する値である95パーセンタイル値の点推定値（0.187）は，急性の健康影響を持つ物質の有害性や，ばく露限界値を超える過剰ばく露の評価に重要である．",{"$nulls":3},250,242,256,280,331,83,295,245,247,302,103,276,282,264,86,0]
[null,"For acute agents, the average exposure is not as important as understanding how high the exposure may get because those few high exposures might pose a more important risk to health than average exposures at lower levels.",null,82,"comm.\nExemple","For acute agents, the average exposure is not as important as understanding how high the exposure may get because those few high exposures might pose a more important risk to health than average exposures at lower levels.","Para los agentes agudos la exposición promedio no es tan importante como entender cuan alta puede llegar a ser la exposición. Los escasos picos de exposición elevada pueden ser un mayor riesgo para la salud que las exposiciones promedio inferiores. ","Pour les effets aigus, la valeur d'exposition moyenne n'est pas aussi importante que la valeur maximale qui peut être atteinte car des expositions élevées peu fréquentes sont plus à risque d'affecter la santé qu'une exposition moyenne plus basse.","Im Falle eines Wirkstoffes mit akuten Wirkungen für die Gesundheit ist die Durchschnittsexposition nicht so wichtig als die Einsicht wie hoch eine Exposition werden kann, weil diese wenigen hohen Expositionen können ein bedeutenderes Risiko hervorrufen als Durchschnittsexpositionen mit niedrigeren Konzentrationen. ","Nel caso di sostanze aventi un effetto acuto, la breve esposizione a picchi di concentrazione puo' avere un rischio piu' importante che una piu' lunga esposizione a un livello medio piu' basso. ","对于急性毒性物质，峰值水平比平均接触水平更重要，因为偶尔的高浓度的接触可能会比更低的平均接触水平导致更严重的健康效应。"," Para agentes químicos com efeitos agudos, a média da exposição não é tão importante quanto a compreensão do quão alta pode ser a exposição, pois essas poucas altas exposições podem representar um risco mais importante à saúde do que a exposição média a níveis mais baixos.","V případě látky působící akutním účinkem je významný především údaj o nárazových krátkodobých koncentracích (méně významný je údaj o průměrných expozicích). Omezené krátkodobé vysoké expozice mohou představovat vyšší riziko než průměrné expozice nižším dávkám. ","एक्युट एजेन्टों के लिए, औसत एक्स्पोजर उतना महत्वपूर्ण नहीं है जितना कि एक्स्पोजर कितना ऊंचा रहेगा क्योंकि ऐसे कुछ ऊंचे एक्स्पोजर, कम स्तर के औसत एक्स्पोजरों के मुकालबे स्वास्थ्य के लिए अधिक जोखिमप्रद साबित हो सकते हैं.","In het geval van een acuut agens is de gemiddelde blootstelling lang niet zo belangrijk als inzien hoe hoog de blootstelling zou kunnen worden, omdat die enkele hoge blootstellingen een belangrijker risico voor de gezondheid kunnen vormen dan gemiddelde blootstellingen in lagere concentraties.","급성요소에서, 이러한 몇몇의 높은 노출이 낮은 수준에서 평균 노출보다 건강에 더 중요한 위험을 일으킬 수 있기 때문에 평균 노출은 얼마나 노출수준이 높은가의 개념만큼 중요하지 않습니다. ","For akutt effekter, er gjennomsnittlig eksponering et dårlig mål, da det er viktig å forstå hvor høy eksponering kan bli, da disse kan utgjøre en større helserisiko enn den gjennomsnittlige eksponering på et lavere nivå.","Akut etkenlerde / ajanlarda, ortalama maruz kalma miktarının, yüksek miktardaki maruz kalmalara kıyaslanması pek bir önem ifade etmeyebilir çünkü kısa süreli de olsa yüksek miktardaki maruz kalmalar sağlık açısından çok tehlikeli olabilir."," Для очень вредных веществ, понятие среднего воздействия вещества менее важно, нежели понимание какие высокие концентрации могут быть. Воздействия этих высоких концентраций могут представлять более важный риск для здоровья, чем среднее воздействие при более низких уровнях.","急性影響物質の場合，時々起きる高いばく露がそれより低い定常的なばく露よりも高い健康リスクとなることから考えて，ばく露の平均値は，ばく露が時として如何に高くなるかということより重要性が低い．",{"$nulls":3},221,249,246,316,194,59,273,261,218,294,104,220,239,273,94,0]
[null,"However, there is uncertainty associated with the percentile estimate - to that uncertainty, we can calculate an UTL.",null,83,"comm.\nExemple","However, there is uncertainty associated with the percentile estimate - to that uncertainty, we can calculate an UTL.","No obstante, existe un nivel de incertidumbre asociado al percentil estimado - para corregir esa incertidumbre se calcula el limite superior de tolerancia.","Il y a cependant une incertitude liée à l'estimation des percentiles, incertitude pour laquelle on peut calculer une limite supérieure de tolérance.","Allerdings gibt es eine Unsicherheit mit der 95. Perzentile Punktschätzung - diese Unsicherheit kann mit dem Rechnen einer oberen Toleranzgrenze geschätzt werden. ","Esiste comunque un'incertezza legata alla stima dei percentili, incertezza che si puo' valutare calcolando un limite superiore di tolleranza.","但是该百分位数估计也存在不确定性，对于该不确定性，我们可以计算UTL。","Entretanto, existe uma incerteza associada à estimativa do percentil - incerteza que pode ser avaliada calculando-se o limite de tolerância superior.","Existuje nejistota spojená s odhadem percentilu - pro tuto nejistotu můžeme spočítat UTL.","हालांकि, प्रतिशत अनुमान के साथ अनिश्चितता जुडी है - उस अनिश्चितता के साथ हम युटीएल की गणना कर सकते हैं.","Er is echter onzekerheid verbonden aan deze puntschatting. Deze onzekerheid kan geëvalueerd worden door een Bovenste Tolerantie Limiet (BTL) te berekenen.","그러나 백분율 추정과 관련하여 불확실합니다 - 그 불확실성은 상위 허용 한계를 계산하여 평가할 수 있습니다.","Det er imidlertid usikkerhet knyttet til estimatet av persentilen - denne kan vurderes ved hjelp av ØTG.","Ancak, yüzdesel hesaplamada bir kararsızlık mevcuttur - bu kararsızlık durumunda, UTL hesaplanabilir.","Однако, существует  неуверенность,  связанная с расчитыванием процентиля. Для большей точности можно еще расчитать Верхний Допустимый Предел.","但し，95パーセンタイルの推定には不確実性が伴い，それは上側許容区間の算出により評価できる．",{"$nulls":3},117,155,148,163,141,35,149,89,103,154,60,104,101,141,46,0]
[null,"A tolerance limit enables one to quantify confidence in a percentile estimate. We can be confident that 95 % of the exposures in the exposure distribution are less than  0.359 µg/m³.",null,84,"comm.\nExemple","A tolerance limit enables one to quantify confidence in a percentile estimate. We can be confident that 95 % of the exposures in the exposure distribution are less than  0.359 µg/m³.","El límite de tolerancia permite cuantificar el nivel de confianza en la estimación del percentil. Podemos confiar que el 95% de las exposiciones en la distribución son menores que  0.359 µg/m³."," La limite de tolérance permet de quantifier la confiance dans l'estimation d'un percentile. Ainsi, on peut être certain à 95 % que 95% des valeurs d'exposition sont inférieures à 0.359 µg/m³.","Eine Toleranzgrenze ermöglicht einem, die Konfidenz quantitativ zu bestimmen, und zwar in der Schätzung eines Perzentiles. Wir können sicher sein dass 95% der Expositionswerte unter 0.359 µg/m³ liegen.","Il limite di tolleranza permette di valutare la confidenza della stima di un percentile. Quindi possiamo essere certi al 95% che almeno il 95% dei valori del profilo sono inferiori 0,359 µg/m³.","容许限值可以通过一个百分位数的估计来确定其可信度。我们有信心认为在该接触分布中有95%的接触浓度是低于0.359µg/m³的。","Um limite de tolerância nos permite quantificar o nível de confiança em uma estiamtiva do percentil. Podemos ter a certeza de que 95% das exposições de uma distribuição são inferiores a 0,359 μ g / m³.","Toleranční limit umožňuje kvantifikovat jistotu v percentilním odhadu. Je 95% jistota, že 95% expozic v distribuci je méně než 0.359 µg/m³. ","सह्यता सीमा प्रतिशत अनुमान में विश्वास की मात्रा दर्शाता है. हम इस बात से आश्वस्त हो सकते हैं कि एक्स्पोजर वितरण में एक्स्पोजर के 95%, 0.359 µg/m³ से कम है.","Een tolerantie limiet stelt ons in staat om het vertrouwen in een percentielschatting te kwantificeren. We kunnen er vertrouwen in hebben dat 95% van de bloostellingen in de verdeling lager zijn dan 0,359 µg/m³.","허용한계는 백분율 추정에 양적 신뢰를 정할 수 있습니다. 노출 분포에서 노출의 95 %가 0.359 μg / m³ 미만이라는 것을 확신할 수 있습니다.","En toleranse grense gjør det mulig å kvantifisere usikkerheten i estimatet av persentilen. Vi kan være sikre på at 95% av eksponeringene i eksponeringsfordelingen er mindre enn 0,359 mg/m³.","Tolerans sınırlaması sayesinde güvenirlik ölçüsünü yüzdesel olarak hesaplanabilir. Bu doğrultuda güvenilir bir şekilde %95 oranında ki maruz kalmalar (ekspoziteler) maruz kalma dağılımından 0.359 µg/m³ daha azdır.","Допустимый лимит позволяет вычислить достоверность в виде расчитывания персентиля. Мы можем быть уверенны, что 95% полученных воздействий вещества в данных респеределения меньше, чем 0,359 мг/м3.","許容区間は，95パーセンタイル値の推定値の信頼性を定量的に示す。ここでは、ばく露分布の少なくとも95%が0.359 µg/m³より小さいことが，95%の信頼性をもって言える．",{"$nulls":3},182,193,192,201,193,63,201,140,156,211,84,189,213,195,87,0]
[null,"This is greater than our OEL of 0.15 µg/m³. Therefore we are not 95% certain that the exposure is less than the OEL 95% of the time. (See also Exceedance Fraction)",null,85,"comm.\nExemple","This is greater than our OEL of 0.15 µg/m³. Therefore we are not 95% certain that the exposure is less than the OEL 95% of the time. (See also Exceedance Fraction)","Este valor es mayor que el LEO de 0.15 µg/m³. Por tanto, no hay 95% de certeza que la exposición es menor que el LEO en el 95% del tiempo (Ver fracción excedente).","Cette valeur est supérieure à la VLE = 0.15 µg/m³. Donc, on n'est pas certain à 95%, que 95% du temps, l'exposition est moindre que la VLE. (Voir aussi la fraction de dépassement) ","Das ist grösser als unser MAK-Wert von  0.15 µg/m³. Daher sind wir uns nicht zu 95% sicher ob die Exposition, zu 95% der Zeit, unter dem MAK-Wert liegt. (Siehe auch Überschreitungsanteil)","Questo valore é superiore alla TLV = 0.15 µg/m³. Quindi, non siamo sicuri al 95%, che per il 95% del tempo, l'esposizione é inferiore alla TLV (Vedi anche la frazione eccedente)","这是大于我们的OEL即0.15µg/m³的。因此我们有95%的理由认为该接触不是小于OEL水平的。（见超标比例）","Isso é maior do que o nosso LEO de 0,15 μ g / m³. Portanto, nos não temos 95% de certeza de que a exposição está abaixo do LEO em 95% do tempo. (Veja também Fração Excedente)","Tato hodnota je vyšší než EL 0,15 µg/m³. Nemáme proto 95% jistotu, že expozice je v 95% případů nižší než EL. (viz také Zlomek překročení)","यह हमारे ओइएल के 0.15 µg/m³ से अधिक है. अत: हम 95% आश्वस्त नहीं है कि एक्स्पोजर, समय के ओइएल95% से कम है. (आधिक्य अंश भी देखें.)","Dit is groter dan onze GBB van 0,15 µg/m³. Daarom zijn we niet 95% zeker dat de blootstelling lager is dan de GBB gedurende 95% van de tijd. (Zie ook Overschrijdingsfractie)","이것은 0.15 μg / m³ 의 직업노출기준보다 큽니다. 따라서 이 노출이 95%의 경우 직업노출기준 미만이라고  95% 확신할 수 없습니다 (초과율 섹션을 참조하십시오).","Dette er større enn vår YGV på 0,15 mg/m³. Derfor er vi ikke 95% sikre på at eksponeringen er mindre enn YGV 95% av tiden (se også overskridelsesfraksjon).","Bu değer OEL'den 0.15 µg/m³ daha fazladır. Dolayısı ile %95 emin olmamakla birlikte maruz kalma miktarı her seferinde OEL'den %95 daha azdır (Aşım-kesimi'ne bakınız)","Полученный результат превышает  наш ЛПО 0,15мг/м3. Следовательно нет 95% уверенности, что данное воздействие вещества меньше, чем ЛПО в 95% случаев (СМ. Фракция превышения)","この値はばく露限界値0.15 µg/m³より大きい．従って，ばく露の95%がばく露限界値より小さいと95%の信頼性で言うことはできない．",{"$nulls":3},163,163,180,187,177,56,174,138,128,173,97,155,165,172,68,0]
[null,"Exceedance Fraction is the proportion of an exposure profile that exceeds a criterion such as an OEL. The uncertainty in the exceedance fraction point estimate is delimited by calculating a confidence interval.",null,86,"comm.\nExemple","Exceedance Fraction is the proportion of an exposure profile that exceeds a criterion such as an OEL. The uncertainty in the exceedance fraction point estimate is delimited by calculating a confidence interval.","La fracción excedente FE es una proporción del perfil de exposición que excede el criterio definido, como el LEO. La incertidumbre al estimar su punto se delimita calculando los intervalos de confianza.","La fraction de dépassement est la proportion des données d'exposition qui dépassent un critère donné tel la VLE. L'incertitude associée à la valeur estimée pour la fraction de dépassement est déterminée par le calcul d'un intervalle de confiance. ","Der Überschreitungsanteil ist der Anteil des Expositionsprofils, der ein gewisses Kriterium überschreitet, so wie ein MAK-Wert. Die Unsicherheit der Punktschätzung des Überschreitungsanteils ist durch das Rechnen eines Konfidenzintervalls begrenzt.","La frazione eccedente rappresenta la percentuale dei valori di un profilo d'esposizione superiori al valore limite di soglia (TLV). L'incertezza associata alla stima della frazione eccedente é determinata grazie all'intervallo di confidenza.","超标比例是在一个接触监测数据中超过某个标准如OEL水平的部分。超标比例点估计值的不确定性可以通过计算可信区间来进行界定。","Fração Excedente é a porção de um perfil de exposição que excede um critério definido como um LEO. A incerteza associada na estimativa do ponto de fração excedente é delimitado pelo cálculo de um intervalo de confiança.","Zlomek překročení je část expozičního profilu, který překračuje kritéria typu EL. Nejistota v odhadu zlomku překročení je omezena intervalem spolehlivosti.","आधिक्य अंश,एक्स्पोजर प्रोफाइल का वह हिस्सा है जो ओइएल जैसे मानदंडों से अधिक हो. आधिक्य अंश पाइन्ट अनुमान में अनिश्चितता, विश्वास अंतर की गणना करने पर कम की जा सकती है.","De overschrijdingsfractie is de proportie van een blootstellingsprofiel die een criterium zoals de GBB overschrijdt. Aan de onzekerheid in de puntschatting van de overschrijdingsfractie wordt tegemoet gekomen door een betrouwbaarheidsinterval te berekenen.","초과율은 예를들어 직업노출기준을 초과하는 노출 개요서의 비율입니다. 초과율 점 추정의 불확실성은 신뢰구간을 계산하여 구분되어집니다.","\"Overskridelses fraksjon\" er andelen av en eksponeringsprofilen som overstiger YGV. Usikkerheten i punktestimatet til overskridelsesfraksjonen er vurdert ved å beregne et konfidensintervall.","Aşım-kesimi üst miktrarın üzerindeki maruz kalma kesitidir. Bu önceden verilmiş olan bir kriterin (bu OEL'de olabilir) aşılması durumudur.","Фракция превышения -это пропорция профиля воздействия вещества, которая превышает данный ЛПО. Неточность в оценке фракции превышения ограничивается расчитыванием интервала достоверности.","超過割合とも言い，ばく露分布のうちばく露限界値を超えているものの割合を示す．超過割合の点推定値の不確実性は，その信頼区間の算出により数値化できる．",{"$nulls":3},210,202,247,248,241,60,219,155,167,256,73,190,138,186,73,0]
[null,"In the present case our most likley estimate is that 9.1% of the exposures in the exposure profile will exceed the OEL; however, there is some error associated with that estimate. ",null,87,"comm.\nExemple","In the present case our most likley estimate is that 9.1% of the exposures in the exposure profile will exceed the OEL; however, there is some error associated with that estimate. ","En el caso actual la estimación más probable es que 9.1% de las mediciones del perfil de exposición excederá LEO. Pero hay algún nivel de error en esta estimación.  ","Dans le cas présent, l'estimé le plus probable est que 9.1% des valeurs d'exposition dépassent la VLE; cependant, il y a une certaine erreur associée à cet estimé. ","Im vorliegenden Fall ist unsere höchstwahrscheinlichste Schätzung dass 9.1% der Expositionswerte die MAK überschreiten werden; allerdings gibt es einige Fehler die mit der Schätzung verbunden sind.","In questo caso, la stima piu' probabile é che 9.1% dei valori d'esposizione superano la TLV; tuttavia, persiste un certo errore associato a questa stima.","在该案例中，我们的最大可能估计是在该接触资料中有9.1%的接触数据超过OEL；但是，此估计也存在一些误差。","No presente caso, a estimativa mais provável é que 9,1% das exposições no perfil de exposição excederá o LEO; no entanto, existem alguns erros associados a essa estimativa.","Dle našeho odhadu překročí 9,1% expozic v daném expozičním profilu EL; odhad je však zatížen chybou.","इस मामले में हमारा संभावित अनुमान यह है कि एक्स्पोजर प्रोफाईल में एक्स्पोजर का 9.1%, ओइएल से बढ जाएगा; हालांकि, ऐसा लगता है कि इसमें अनुमान से जुडी कोई त्रुटि है.","In het huidige voorbeeld is onze meest waarschijnlijke schatting dat 9,1% van de blootstellingen uit het blootstellingsprofiel de GBB zullen overschrijden; er echter een onzekerheid verbonden aan deze schatting.","현재의 경우에 가장 가능성이 있는 추정은 노출 개요서에서 노출의 9.1 %가 직업노출기준을 초과할 수있다는 것입니다. 하지만, 이 추정과 관련된 몇 가지 오류가 있습니다.","I eksemplet vårt er det mest sannsynlig at 9,1% av eksponeringen i eksponerings profilen vil overstige YGV, men det er noe usikkerhet knyttet til dette anslaget.","Mevcut koşullarda en iyi ihtimal ile %9,1 oranındaki maruziyetler OEL sınırının üzerinde olacaktır. Fakat hesaplamada bir hata meydana gelmiştir.","В данном случае, наш самый вероятный расчет - это 9,1% профессионального облучения в данном профиле превысит ЛПО. Тем не менее, есть некоторые ошибки, связанные с этой оценкой.","この場合，ばく露分布のうち9.1%がばく露限界値を超えていると予測できる．但し，その推定には誤差が伴う．",{"$nulls":3},180,165,164,197,153,53,172,100,162,211,95,161,145,176,52,0]
[null,"To quantify the confidence in the exceedance fraction estimate, we can calculate confidence limits (2.83%; 23.4%)",null,88,"comm.\nExemple","To quantify the confidence in the exceedance fraction estimate, we can calculate confidence limits (2.83%; 23.4%)","Los límites de confianza (2.83%-23.4%) se estiman para cuantificar el error estimado de la FE.  ","Pour évaluer l'erreur associée à cet estimé, il faut calculer les limites de confiance (2,83%; 23,4%). ","Um die Konfidenz für die Überschreitungsanteilschätzung quantitativ bestimmen zu können, können wir Konfidenzgrenzen (2.83%; 23.4%) rechnen.","Per valutare l'errore associato a questa stima, bisogna calcolare i limiti dell'intervallo di confidenza (2.38%; 23,4%).","在超标比例估计中为了定量其可信度，我们可以计算可信限（2.83%；23.4%）。","Para quantificar a confiança na estimativa da fração excedente, podemos calcular limites de confiança (2,83%; 23,4%).","Pro kvatifikaci jistoty v odhadu zlomku překročení je možné vypočítat intervaly spolehlivosti (2.83%; 23.4%)","आधिक्य अंश अनुमान में विश्वास की मात्रा का पता लगाने हेतु हम विश्वास सीमा (2.83% ; 23.4%) की गणना कर सकते हैं.","Om het vertrouwen in de schatting van de overschrijdingsfractie te kwantificeren, kunnen we betrouwbaarheidslimieten berekenen (2,83%; 23,4%)","초과율 추정에서 신뢰를 양적화하기 위해, 신뢰 한계를 계산할 수 있습니다 (2.83%; 23.4%)","For å vurdere usikkerheten i punktestimatet til overskridelsesfraksjonen, kan vi beregne dets konfidensintervall (2,83%; 23,4%)","Aşım-kesimi hesabını güvenilir bir şekilde ölçümlendirebilmek için güvenirlik sınırı (%2,83; %23,4)  olarak hesaplama yapılmıştır.","Для количественной оценки достоверности оценки фракции превышения, мы можем вычислить доверительный интервал","超過割合の推定値の信頼性を数値化するために，信頼区間が計算される（2.82%; 23.4%）",{"$nulls":3},113,96,103,140,120,40,117,108,110,141,55,127,130,108,46,0]
[null,{"$f":"Translation(D100,trad,Language)","v":"Limit of Quantification"},null,89,"Liste","Limit of Quantification","Limite de cuantificación","Limite de Quantification","Quantifikationsgrenze","Limite di quantificazione","定量分析限值","Limite de quantificação","Kvantifikační limit","मात्रा की सीमा","Kwantificatielimiet","정량한계","Kvantifiseringsgrense","Miktar Ölçümü Sınırı","Предел количественного анализа","定量下限値",{"$nulls":3},23,24,24,21,25,6,23,19,14,19,4,21,20,30,5,0]
[null,"Limit of Quantification / 2",null,90,"Liste","Limit of Quantification / 2","Limite de cuantificación/2","Limite de Quantification / 2","Quantifikationsgrenze/ 2","Limite di quantificazione / 2","定量分析限值/2","Limite de quantificação / 2","Kvantifikační limit / 2","मात्रा की सीमा / 2","Kwantificatielimiet / 2","정량한계 / 2","Kvantifiseringsgrense / 2","Miktar Ölçümü Sınırı / 2","Предел количественного анализа / 2","定量下限値/2",{"$nulls":3},27,26,28,24,29,8,27,23,18,23,8,25,24,34,7,0]
[null,"Limit of Quantification / 1.414",null,91,"Liste","Limit of Quantification / 1.414","Limite de cuantificación/1,414","Limite de Quantification / 1,414","Quantifikationsgrenze/ 1,414","Limite di quantificazione / 1,414","定量分析限值/1.414","Limite de quantificação / 1,414","Kvantifikační limit / 1, 414","मात्रा की सीमा / 1,414","Kwantificatielimiet / 1,414","정량한계 / 1.414","Kvantifiseringsgrense / 1,414","Miktar Ölçümü Sınırı / 1,414","Предел количественного анализа / 1.414","定量下限値/1.414",{"$nulls":3},31,30,32,28,33,12,31,28,22,27,12,29,28,38,11,0]
[null,"Yes",null,92,"VB","Yes","Si","Oui","Ja","Si","Yes","Sim","Ano","हां","Ja","예","Ja","Evet","Да","Yes",{"$nulls":3},3,2,3,2,2,3,3,3,3,2,1,2,4,2,3,0]
[null,"No",null,93,"VB","No","No","Non","Nein","No","No","Não","Ne","नहीं","Neen","아니오","Nei","Hayır","Нет","No",{"$nulls":3},2,2,3,4,2,2,3,2,4,4,3,3,5,3,2,0]
[null,"Do you really want to print ?",null,94,"VB","Do you really want to print ?","Está seguro de que desea imprimir ?","Voulez-vous vraiment imprimer ?","Wollen Sie wirklich drucken ?","Desideri stampare ?","Do you really want to print ?","Você realmente deseja imprimir ?","Opravdu chcete tisknout?","क्या आप वास्तव में मुद्रण करना चाहते हैं ?","Wil je echt afdrukken?","정말 인쇄하기를 원하십니까?","Vil du virkelig skrive ut?","Çıktı almak istiyormusunuz?","Хотите Вы распечатать?","印刷しますか？",{"$nulls":3},29,35,31,29,19,29,32,24,42,22,15,26,27,22,7,0]
[null,"Printing !",null,95,"VB","Printing !","Impresión !","Impression !","Drucken !","Stampa !","Printing !","Imprensa !","Tisk!","मुद्रण","Bezig met afdrukken!","인쇄!","Utskrift!","Çıktı al!","Печатается!","印刷！",{"$nulls":3},10,11,12,9,8,10,10,5,6,20,3,9,9,11,3,0]
[null,"English",null,96,"intro","English","Español","Français","Deutsch","Italiano","Chinese","Portuguese","Česky","अंग्रेजी","Engels","영어","Norsk","İngilizce","Английский","英語",{"$nulls":3},7,7,8,7,8,7,10,5,8,6,2,5,9,10,2,0]
[null,"Concentration",null,97,"box","Concentration","Concentración","Concentration","Konzentration","Concentrazione","集中","Concentração","Koncentrace","एकाग्रता","Concentratie","중요: 이 파일을 열 때 매크로를 활성화함.","Konsentrasjon","Yoğunluk","Концентрация","濃度",{"$nulls":3},13,13,13,13,14,2,12,11,8,12,24,13,8,12,2,0]
[null,"Enable macros when opening this file",null,98,null,"Enable macros when opening this file","Habilite los macros cuando abra este archivo.","Activer les macros à l'ouverture du fichier.   ","Beim Öffnen der Datei Makros aktivieren. \n","Attivare le macro all'apertura del file               "," 注意：打开该文档时请启用宏。","Ativar macros quando abrir este arquivo.  ","Při otevření tohoto souboru povolte makra. ","इस फ़ाइल खोलने जब स्थूल सक्षम है. ","Macro's inschakelen bij het openen van dit bestand","이 파일을 열 때 매크로를 활성화함.","Aktiver makroer når du åpner denne filen","Dosyayı açarken makroları etkinleştirin","Запускайте работу макросов при открывании документа","ファイルを開く時マクロを有効にしてください",{"$nulls":3},36,45,47,42,54,15,42,43,34,50,20,40,39,51,21,0]
[null,"A full discussion on how to analyze and interpret exposure monitoring data can be found in the publication\n",null,99,"intro","A full discussion on how to analyze and interpret exposure monitoring data can be found in the publication\n","A full discussion on how to analyze and interpret exposure monitoring data can be found in the publication\n","A full discussion on how to analyze and interpret exposure monitoring data can be found in the publication\n","A full discussion on how to analyze and interpret exposure monitoring data can be found in the publication\n","A full discussion on how to analyze and interpret exposure monitoring data can be found in the publication\n","A full discussion on how to analyze and interpret exposure monitoring data can be found in the publication\n","A full discussion on how to analyze and interpret exposure monitoring data can be found in the publication\n","A full discussion on how to analyze and interpret exposure monitoring data can be found in the publication\n","A full discussion on how to analyze and interpret exposure monitoring data can be found in the publication\n","A full discussion on how to analyze and interpret exposure monitoring data can be found in the publication\n","A full discussion on how to analyze and interpret exposure monitoring data can be found in the publication\n","En full diskusjon om hvordan man skal analysere og tolke eksponering overvåkingsdata kan finnes i publikasjonen","Maruz kalma gözlemi verisinin detaylı olarak analizi ve yorumu hakkında daha kapsamlı bilgilere yayımlanmiş eserler üzerinden ulaşabilirsiniz","Полной описание анализа и интерпритации данных контроля воздействия вредных веществ может быть найден в следующей побликации:","この本では，ばく露測定データの解析や解釈が詳細に議論されている．",{"$nulls":3},107,107,107,107,107,107,107,107,107,107,107,111,141,125,32,0]
[null,"Steven D. Jahn, William H. Bullock, and Joselito S. Ignacio (editors)\nA Strategy for Assessing and Managing Occupational Exposures, 4rd Edition. Fairfax, VA: AIHA Press, 2015",null,100,"intro","Steven D. Jahn, William H. Bullock, and Joselito S. Ignacio (editors)\nA Strategy for Assessing and Managing Occupational Exposures, 4rd Edition. Fairfax, VA: AIHA Press, 2015","Steven D. Jahn, William H. Bullock, and Joselito S. Ignacio (editors)\nA Strategy for Assessing and Managing Occupational Exposures, 4rd Edition. Fairfax, VA: AIHA Press, 2015","Steven D. Jahn, William H. Bullock, and Joselito S. Ignacio (editors)\nA Strategy for Assessing and Managing Occupational Exposures, 4rd Edition. Fairfax, VA: AIHA Press, 2015","Steven D. Jahn, William H. Bullock, and Joselito S. Ignacio (editors)\nA Strategy for Assessing and Managing Occupational Exposures, 4rd Edition. Fairfax, VA: AIHA Press, 2015","Steven D. Jahn, William H. Bullock, and Joselito S. Ignacio (editors)\nA Strategy for Assessing and Managing Occupational Exposures, 4rd Edition. Fairfax, VA: AIHA Press, 2015","Steven D. Jahn, William H. Bullock, and Joselito S. Ignacio (editors)\nA Strategy for Assessing and Managing Occupational Exposures, 4rd Edition. Fairfax, VA: AIHA Press, 2015","Steven D. Jahn, William H. Bullock, and Joselito S. Ignacio (editors)\nA Strategy for Assessing and Managing Occupational Exposures, 4rd Edition. Fairfax, VA: AIHA Press, 2015","Steven D. Jahn, William H. Bullock, and Joselito S. Ignacio (editors)\nA Strategy for Assessing and Managing Occupational Exposures, 4rd Edition. Fairfax, VA: AIHA Press, 2015","Steven D. Jahn, William H. Bullock, and Joselito S. Ignacio (editors)\nA Strategy for Assessing and Managing Occupational Exposures, 4rd Edition. Fairfax, VA: AIHA Press, 2015","Steven D. Jahn, William H. Bullock, and Joselito S. Ignacio (editors)\nA Strategy for Assessing and Managing Occupational Exposures, 4rd Edition. Fairfax, VA: AIHA Press, 2015","Steven D. Jahn, William H. Bullock, and Joselito S. Ignacio (editors)\nA Strategy for Assessing and Managing Occupational Exposures, 4rd Edition. Fairfax, VA: AIHA Press, 2015","Steven D. Jahn, William H. Bullock, and Joselito S. Ignacio (editors)\nA Strategy for Assessing and Managing Occupational Exposures, 4rd Edition. Fairfax, VA: AIHA Press, 2015","Steven D. Jahn, William H. Bullock, and Joselito S. Ignacio (editors)\nA Strategy for Assessing and Managing Occupational Exposures, 4rd Edition. Fairfax, VA: AIHA Press, 2015","Steven D. Jahn, William H. Bullock, and Joselito S. Ignacio (editors)\nA Strategy for Assessing and Managing Occupational Exposures, 4rd Edition. Fairfax, VA: AIHA Press, 2015","Steven D. Jahn, William H. Bullock, and Joselito S. Ignacio (editors)\nA Strategy for Assessing and Managing Occupational Exposures, 4rd Edition. Fairfax, VA: AIHA Press, 2015"]
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{"sheet":"dd","index":8,"n_rows":52,"n_cols":30,"rows_kept":52,"hidden":true}
[]
[null,null,"Estimated Arithmetic Mean - MLE (OLD)",{"$f":"MLE","v":{"v":0.07502000844071018,"d":"0.075"}},{"$nulls":8},"Returns Coeff: n = 2 to 9",null,"Coefficients for CL when n>9",null,null,"Coefficients for size n>9",{"$nulls":4},"Matrix for CL Coefficients when n<10:"]
[null,null,"1,95%LCL LogNorm t",{"$f":"MLE*EXP(-TINV(0.1,Nsamples-1)*(StdLogT/SQRT(Nsamples)))","v":{"v":0.054375364468621616,"d":"0.054"}},{"$nulls":5},"For C LCL","For C UCL","n=",{"$f":"Nsamples","v":15},null,"LCL","UCL","z","0 to 3","\"-6 to <0","\" <  -6",null,"n",2,3,4,5,6,7,8,9]
[null,null,"1,95%UCL LogNorm t",{"$f":"MLE*EXP(TINV(0.1,Nsamples-1)*(StdLogT/SQRT(Nsamples)))","v":{"v":0.10350278515727425,"d":"0.104"}},{"$nulls":4},"a",-0.85033767,0.76766658,"a",{"$f":"HLOOKUP(Nsamples,TableCL,2)","v":0.29158511},"z=",{"$f":"C26","v":1.3329015299928428},{"$f":"AB22","v":-1.3329015299928428},"lookup",1,2,3,null,"a",0.122639,0.17093583,0.20527676,0.23087629,0.25087349,0.26701314,0.28035886,0.29158511]
[{"$nulls":8},"b",-0.5258052,3.8716869,"b",{"$f":"HLOOKUP(Nsamples,TableCL,3)","v":-0.14267075},"Lookup",{"$f":"AA27","v":1},{"$f":"AB27","v":2},"a",0.82705588,0.9159042,null,null,"b",-1.183888,-0.36372227,-0.3756623,-0.32948211,-0.30146272,-0.26555197,-0.21322137,-0.14267075]
[null,"LAND's Exact 95% 1-Sided CI's  (HEWETT AND GAUSER 1997)",{"$nulls":6},"c",0.92416176,0.80598919,"c",{"$f":"HLOOKUP(Nsamples,TableCL,4)","v":-0.37596357},"a",{"$f":"HLOOKUP(O5,R4:T14,2)","v":0.82705588},{"$f":"HLOOKUP(P5,R4:T16,2)","v":0.9159042},"b",0.47348658,0.46749901,null,null,"c",-0.30512797,-0.28537457,-0.33810835,-0.36170947,-0.3787192,-0.38705351,-0.38608727,-0.37596357]
[null,"s(ln x)",{"$f":"IF(StdLogT<0.01,0.01,StdLogT)","v":{"v":0.7077090677879492,"d":"0.707709067788"}},"LCL %ile=",0.05,{"$nulls":3},"d",3.3298209,6.0321019,"d",{"$f":"HLOOKUP(Nsamples,TableCL,5)","v":0.41758212},"b",{"$f":"HLOOKUP(O5,R4:T14,3)","v":0.47348658},{"$f":"HLOOKUP(P5,R4:T16,3)","v":0.46749901},"c",-1.5959026,-1.5978413,null,null,"d",1.025662,0.34851212,0.36738495,0.35945667,0.3687124,0.38401727,0.40265771,0.41758212]
[null,"s(ln x) to use",{"$f":"IF(C7>4,4,C7)","v":{"v":0.7077090677879492,"d":"0.70770906779"}},"UCL %ile=",0.95,{"$nulls":3},"e",0.94348568,0.89998154,"e",{"$f":"HLOOKUP(Nsamples,TableCL,6)","v":0.2072291},"c",{"$f":"HLOOKUP(O5,R4:T14,4)","v":-1.5959026},{"$f":"HLOOKUP(P5,R4:T16,4)","v":-1.5978413},"d",-0.35885104,-0.21867454,null,null,"e",0.30466959,0.16073371,0.20373584,0.21196252,0.22058761,0.22384309,0.22000682,0.2072291]
[{"$nulls":8},"f ",1.3213281,2.012669,"f",{"$f":"HLOOKUP(Nsamples,TableCL,7)","v":0.023635477},"d",{"$f":"HLOOKUP(O5,R4:T14,5)","v":-0.35885104},{"$f":"HLOOKUP(P5,R4:T16,5)","v":-0.21867454},"e",-0.3762358,-0.16711347,null,null,"f",-0.32067478,0.054071371,0.018923968,0.019458266,0.016283799,0.015667728,0.018042944,0.023635477]
[null," MLE",{"$f":"MLE","v":{"v":0.07502000844071018,"d":"0.075"}},"Should be MLE with n, not n-1",{"$nulls":4},"g",0.8155562,0.21978875,"g",{"$f":"HLOOKUP(Nsamples,TableCL,8)","v":-0.073405376},"e",{"$f":"HLOOKUP(O5,R4:T14,6)","v":-0.3762358},{"$f":"HLOOKUP(P5,R4:T16,6)","v":-0.16711347},"f",-0.0059178009,-0.055872009,null,null,"g",-0.1511292,-0.025966434,-0.049770351,-0.053579348,-0.060450757,-0.066696572,-0.071663981,-0.073405376]
[null,"S' ",{"$f":"C7*(SQRT((Nsamples-1)/Nsamples))","v":0.6837119152006461},{"$nulls":5},"h",-1.018148,0.41575588,"h",{"$f":"HLOOKUP(Nsamples,TableCL,9)","v":0.03496479},"f",{"$f":"HLOOKUP(O5,R4:T14,7)","v":-0.0059178009},{"$f":"HLOOKUP(P5,R4:T16,7)","v":-0.055872009},"g",0.052553183,0.078057826,null,null,"h",0.061852348,0.002995818,0.011064939,0.015386764,0.020005908,0.024962675,0.030244939,0.03496479]
[null,"C, LCL",{"$f":"IF(Nsamples>2,L22,L21)","v":-1.6501909361494251},{"$f":"IF(Nsamples>2,J22,J21)","v":2.284869398343076},"C, UCL",{"$nulls":3},"I",0.25248895,0.29258276,"i",{"$f":"HLOOKUP(Nsamples,TableCL,10)","v":0.018251034},"g",{"$f":"HLOOKUP(O5,R4:T14,8)","v":0.052553183},{"$f":"HLOOKUP(P5,R4:T16,8)","v":0.078057826},"h",0.26488682,0.28495322,null,null,"i",0.036997109,-0.0050019868,0.0024343744,0.0042734939,0.0074082789,0.010898192,0.014749941,0.018251034]
[null,"LCL",{"$f":"EXP((LN(MLE))+(C12*(C7/(SQRT(Nsamples-1)))))","v":0.05490653937284466},{"$f":"EXP((LN(MLE))+(D12*(C7/(SQRT(Nsamples-1)))))","v":0.11557531284589541},"UCL",{"$nulls":6},"j",{"$f":"HLOOKUP(Nsamples,TableCL,11)","v":-0.0011924843},"h",{"$f":"HLOOKUP(O5,R4:T14,9)","v":0.26488682},{"$f":"HLOOKUP(P5,R4:T16,9)","v":0.28495322},"i",-0.075413666,-0.073167856,null,null,"j",-0.0023723692,0.0016331608,0.00085720372,0.00075015011,0.00039892655,-4.2375686e-05,-0.00060041754,-0.0011924843]
[null,"Now it seems to be working with Hewett new equation and coefficients",{"$nulls":6},"F1",{"$f":"J4/(((Nsamples-2)^J6))+J5","v":-0.6052613595154868},{"$f":"C8*(K12+(1/((Nsamples-2)^K6)))","v":0.2966058165375389},"k",{"$f":"HLOOKUP(Nsamples,W3:AD14,12)","v":-0.0021651986},"i",{"$f":"HLOOKUP(O5,R4:T14,10)","v":-0.075413666},{"$f":"HLOOKUP(P5,R4:T16,10)","v":-0.073167856},"j",-2.4186812,-2.4074152,null,null,"k",-0.0035624416,0.0014215249,5.0349027E-4,0.00019427452,-0.00027967341,-0.00083411655,-0.0014920275,-0.0021651986]
[{"$nulls":8},"F2",{"$f":"J7/(((Nsamples-2)^J9))+J8","v":1.0558261461613183},{"$f":"K5+(K7/((Nsamples-2)^K6))","v":4.634893942564025},null,null,"j",{"$f":"HLOOKUP(O5,R4:T16,11)","v":-2.4186812},{"$f":"HLOOKUP(P5,R4:T16,11)","v":-2.4074152},"k",0.54932221,0.54932221]
[null,"90% CI on Exceedence Estimate (Hewett from Odeh and Owen)",{"$nulls":6},"F3",{"$f":"J10/(((Nsamples-2)^J12))+J11","v":-0.5913764047430357},{"$f":"K14*(1-(K8*EXP(-K9*K14)))","v":0.14966150512412668},null,null,"k",{"$f":"HLOOKUP(O5,R4:T16,12)","v":0.54932221},{"$f":"HLOOKUP(P5,R4:T16,12)","v":0.54932221},"l ",-1.0076516,-1.0076516]
[null,null,"LCL","UCL",{"$nulls":4},"F4",{"$f":"-0.6226/(((Nsamples-2)^0.2426))+1.147","v":0.8128307691374416},{"$f":"1+(K10*EXP(-K11*K14))","v":1.194289875118858},null,null,"l",{"$f":"HLOOKUP(O5,R4:T16,13)","v":-1.0076516},{"$f":"HLOOKUP(P5,R4:T16,13)","v":-1.0076516}]
[null,"Calculated",{"$f":"IF(Nsamples<10,F29*100,G29*100)","v":2.824942123635091},{"$f":"IF(Nsamples<10,F30*100,G30*100)","v":23.359149438612935},{"$nulls":4},"F5",null,{"$f":"K15*K16/K17","v":0.5808181229584607}]
[null,"if CL>0.999",{"$f":"IF(C18>99.9,\">99.9\",C18)","v":2.824942123635091},{"$f":"IF(D18>99.9,\">99.9\",D18)","v":23.359149438612935},{"$nulls":18},"CL if n > 9"]
[null,"if CL<0.001",{"$f":"IF(C18<0.1,\"<0.1\",C19)","v":2.824942123635091},{"$f":"IF(D18<0.1,\"<0.1\",D19)","v":23.359149438612935},{"$nulls":4},"n","C, UCL","n","C, LCL",{"$nulls":10},"LCL","UCL",null,"Lookup rule for CL"]
[null,"if Z>3",{"$f":"IF(D26>3,\"<0.1\",C20)","v":2.824942123635091},{"$f":"IF(D27>3,\">99.9\",D20)","v":23.359149438612935},{"$nulls":4},"0 to 2","NA","0 to 2","NA",{"$nulls":9},"F1",{"$f":"(O6/((Nsamples-1)^O7))+O8","v":-1.358842420025266},{"$f":"(P6/((Nsamples-1)^P7))+P8","v":-1.3311331244700866},null,null,"LCL","UCL"]
[null,"if Z<-6",{"$f":"IF(D26<-6,C24,C21)","v":2.824942123635091},{"$f":"IF(D27<-6,D24,D21)","v":23.359149438612935},{"$nulls":4},"3 to 1001",{"$f":"1.645+K4/(Nsamples-2)+K18","v":2.284869398343076},"3 to 1001",{"$f":"-0.74295/(Nsamples-2)-1.64765+C8*(J16+J15*EXP(J14*(C8^J17)))","v":-1.6501909361494251},{"$nulls":9},"F2",{"$f":"(O9*(Nsamples-1)^O10)*EXP(O11*(LN(Nsamples-1))^2)","v":-0.12758518646310232},{"$f":"(P9*(Nsamples-1)^P10)*EXP(P11*(LN(Nsamples-1))^2)","v":-0.09533861912657889},null,"z=",{"$f":"O4","v":1.3329015299928428},{"$f":"-AA22","v":-1.3329015299928428}]
[{"$nulls":21},"F3",{"$f":"(O12/(Nsamples-1)^O13)+O14","v":-0.04929176287642642},{"$f":"(P12/(Nsamples-1)^P13)+P14","v":-0.036369910045817314},null,"\"<=3",{"$f":"IF(AA22<=3,1,0)","v":1},{"$f":"IF(AB22<=3,1,0)","v":1}]
[null,null,{"$f":"CONCATENATE(\">\",FIXED(C18,3))","v":">2,825"},{"$f":"CONCATENATE(\"<\",FIXED(D18,3))","v":"<23,359"},{"$nulls":17},"F4",{"$f":"(O15/(Nsamples-1)^O16)+O17","v":-1.5751766601913921},{"$f":"(P15/(Nsamples-1)^P16)+P17","v":-1.5725331793853576},null,"<0",{"$f":"IF(AA22<0,1,0)","v":0},{"$f":"IF(AB22<0,1,0)","v":1}]
[{"$nulls":9},"OLD HEWETT LAND METHOD COEFFICIENTS - NOT USED",{"$nulls":11},"CL if n>9",{"$f":"(1+EXP(-(W21*O4+W22*O4^2+W23*O4^3)))^W24","v":0.02824942123635091},{"$f":"(1+EXP(-(X21*P4+X22*P4^2+X23*P4^3)))^X24","v":0.7664085056138706},null,"<-6",{"$f":"IF(AA22<-6,1,0)","v":0},{"$f":"IF(AB22<-6,1,0)","v":0}]
[null,"z=",{"$f":"IF(D26<-6,-6,D26)","v":1.3329015299928428},{"$f":"(LN(OEL)-MeanLogT)/StdLogT","v":1.3329015299928428},{"$nulls":5},"coefficients for C, 95% UCL"]
[null,"\"-z=",{"$f":"IF(D27<-6,-6,D27)","v":-1.3329015299928428},{"$f":"-D26","v":-1.3329015299928428},null,"CI:",null,null,"n=",3,4,5,6,7,"8 to 60",{"$nulls":10},"Lookup",{"$f":"SUM(AA23:AA26)","v":1},{"$f":"SUM(AB23:AB26)","v":2}]
[null,"%>OEL = ",{"$f":"1-NORMSDIST(C26)","v":0.09128206021260166},null,null,"n<10","n>9",null,"a",2.3828099,2.0366181,1.9107517,1.8365941,1.7994842,1.642361]
[null,"90%LCL=",{"$f":"C22","v":2.824942123635091},null,"LCL",{"$f":"(M4+(M6*C26)+(M8*(C26^2))+(M10*(C26^3))+(M12*(C26^4))+(M14*(C26^5)))/(1+(M5*C26)+(M7*(C26^2))+(M9*(C26^3))+(M11*(C26^4))+(M13*(C26^5)))","v":0.019439557980234685},{"$f":"W25","v":0.02824942123635091},null,"b",-1.9078016,-1.6251828,-0.75392424,0.12293613,-0.66799472,-0.089895706]
[null,"90%UCL=",{"$f":"D22","v":23.359149438612935},null,"UCL",{"$f":"1-((M4+(M6*C27)+(M8*(C27^2))+(M10*(C27^3))+(M12*(C27^4))+(M14*(C27^5)))/(1+(M5*C27)+(M7*(C27^2))+(M9*(C27^3))+(M11*(C27^4))+(M13*(C27^5))))","v":0.2962851305430325},{"$f":"1-X25","v":0.23359149438612936},null,"c",-1.2992597,-1.6229194,-0.42339524,1.3030195,-0.44540781,2.858099]
[{"$nulls":8},"d",5.2917837,2.6423742,0.89103098,1.5345558,0.85685751,0.69351183]
[null,null,"Hewett's Land's Exact Calculator",{"$nulls":5},"e",7.986645,4.0754459,2.7606354,2.6593492,2.02724,-40.990924]
[null,null,"Estimation of the","Estimation of the",{"$nulls":4},"f",-0.68237045,-1.0014933,-0.18397782,-0.48014164,0.11982844,5.2690665]
[null,null,"95% LCL C-factor","95% UCL C-factor",null,"GM",{"$f":"GeoMean","v":{"v":0.0584,"d":"0.0584000000"}},"range:>0.0","g",31.32989,3.4090807,0.13008099,4.8166929,0.48077011,-0.13243949]
[null,"A",-0.85033767,0.76766658,null,"GSD",{"$f":"GeoStd","v":{"v":2.03,"d":"2.0300000000"}},"range: 1.01-54.5","h",0.54527619,0.2945552,0.053432081,0.0039733022,0.023989184,182.18949]
[null,"B",-0.5258052,3.8716869,null,"n",{"$f":"Nsamples","v":15},"range: 3 - 1001","i",14.16984,0.62956063,0.53746226,-1.6148013,1.065744,24.118101]
[null,"C",0.92416176,0.80598919,{"$nulls":4},"j",-0.066913335,-0.031880045,-0.0038110232,0,0,1.588055]
[null,"D",3.3298209,6.0321019,null,"95%LCL =",{"$f":"EXP(LN(GeoMean)+0.5*LN(GeoStd)^2+C51*LN(GeoStd)/SQRT(Nsamples-1))","v":0.054910036525045225}]
[null,"E",0.94348568,0.89998154,null,"95%UCL =",{"$f":"EXP(LN(GeoMean)+0.5*LN(GeoStd)^2+D51*LN(GeoStd)/SQRT(Nsamples-1))","v":0.11563304581287304}]
[null,"F",1.3213281,2.012669,{"$nulls":5},"Coefficients for Land's C, 95% LCL"]
[null,"G",0.8155562,0.21978875,{"$nulls":5},3,4,5,"6 to 60"]
[null,"H",-1.018148,0.41575588,null,"PDC data:",52,null,null,-2.3865193,-2.0397149,-1.9080983,-1.6652843]
[null,"I",0.25248895,0.29258276,null,null,114,null,null,1.7079129,1.1478581,0.92104952,0.10902402]
[{"$nulls":6},205,null,null,-0.97733458,-0.69548849,-0.58741405,0.41441365]
[null,"F1",{"$f":"C35/(Nsamples-2)^C37+C36","v":{"v":-0.6052613595154868,"d":"-0.605261"}},{"$f":"(LN(G35)*(D43+1/(Nsamples-2)^D37))","v":{"v":0.29674274937991885,"d":"0.296743"}},null,null,365,null,null,-0.036191266,-0.018545416,-0.009714496,-0.41101237]
[null,"F2",{"$f":"C38/(Nsamples-2)^C40+C39","v":{"v":1.0558261461613183,"d":"1.055826"}},{"$f":"(D36+D38/(Nsamples-2)^D37)","v":{"v":4.634893942564025,"d":"4.634894"}},null,null,780,null,null,-0.62035479,-0.52301624,-0.49022279,-16.464546]
[null,"F3",{"$f":"C41/(Nsamples-2)^C43+C42","v":{"v":-0.5913764047430357,"d":"-0.591376"}},{"$f":"(D45*(1-D39*EXP(-D40*D45)))","v":{"v":0.14977110980099964,"d":"0.149771"}},{"$nulls":8},4.2113052]
[null,"F4",{"$f":"-0.6226/(Nsamples-2)^0.2426+1.147","v":{"v":0.8128307691374416,"d":"0.812831"}},{"$f":"(1+D41*EXP(-D42*D45))","v":{"v":1.194278814387863,"d":"1.194279"}},null,"n =",5,{"$nulls":5},0.066100924]
[null,"F5",null,{"$f":"(D46*D47/D48)","v":{"v":0.5812488685429362,"d":"0.581249"}},null,"gm =",203.1468,{"$nulls":5},55.619447]
[{"$nulls":5},"gsd =",2.8352,{"$nulls":5},-7.8131037]
[null,"C-factor",{"$f":"-0.74295/(Nsamples-2)-1.64765+LN(GeoStd)*(C47+C46*EXP(C45*LN(GeoStd)^C48))","v":{"v":-1.6502468873636775,"d":"-1.650247"}},{"$f":"1.645+D35/(Nsamples-2)+D49","v":{"v":2.2853001439275515,"d":"2.285300"}},null,"John, plug in the above numbers and you should get ",{"$nulls":6},-0.22232527]
[{"$nulls":5},"( 155.8902 - 4980.5367 ) as the 90% CI.  "]

{"sheet":"MVUE","index":9,"n_rows":18,"n_cols":8,"rows_kept":18,"hidden":true}
[null,"Calculate MVUE"]
[]
[null,"Mean Ln(Data)",{"$f":"MeanLogT","v":{"v":-2.8404264841302473,"d":"-2.840"}},{"$f":"Nsamples","v":15},"n"]
[null,"SD Ln(Data)",{"$f":"StdLogT","v":{"v":0.7077090677879492,"d":"0.708"}},{"$f":"0.5*StdLogT^2","v":0.25042606231464404},"SD^2/2"]
[]
[null,"Check calc",1,1,null,"PEP"]
[null,"term 1",{"$f":"(Nsamples-1)*(((StdLogT)^2)/2)/Nsamples","v":0.23373099149366774},{"$f":"(Nsamples-1)*$D$4/Nsamples","v":0.23373099149366774},null,"Z (95%)",{"$f":"NORMSINV(0.95)","v":1.6448536269514715}]
[null,"term 2",{"$f":"((Nsamples-1)^3)*((((StdLogT)^2)/2)^2)/(FACT(2)*((Nsamples)^2)*(Nsamples+1))","v":0.023900702168268187},{"$f":"((Nsamples-1)^3)*(($D$4)^2)/((FACT(2))*((Nsamples)^2)*(Nsamples+1))","v":0.023900702168268187},null,"G",{"$f":"NORMSINV(LOGNORMDIST(OEL,MeanLogT,StdLogT))","v":1.3329015299928433},{"$f":"LOGNORMDIST(OEL,MeanLogT,StdLogT)","v":0.9087179397873983}]
[null,"term 3",{"$f":"((Nsamples-1)^5)*((((StdLogT)^2)/2)^3)/(FACT(3)*((Nsamples)^3)*(Nsamples+1)*(Nsamples+3))","v":0.001448309026158861},{"$f":"((Nsamples-1)^5)*(($D$4)^3)/((FACT(3))*((Nsamples)^3)*(Nsamples+1)*(Nsamples+3))","v":0.001448309026158861},null,"A",{"$f":"1/(2*Nsamples-3)-1/NORMSINV(0.95)^2","v":-0.3325744724311584}]
[null,"term 4",{"$f":"((Nsamples-1)^7)*((((StdLogT)^2)/2)^4)/(FACT(4)*((Nsamples)^4)*(Nsamples+1)*(Nsamples+3)*(Nsamples+5))","v":5.9240073317834329E-5},{"$f":"((Nsamples-1)^7)*(($D$4)^4)/((FACT(4))*((Nsamples)^4)*(Nsamples+1)*(Nsamples+3)*(Nsamples+5))","v":5.9240073317834329E-5},null,"B",{"$f":"2*$G$8/NORMSINV(0.95)^2*SQRT((2*Nsamples-3)/(2*Nsamples-2))","v":0.9675566784720235}]
[null,"term 5",{"$f":"((Nsamples-1)^9)*((((StdLogT)^2)/2)^5)/(FACT(5)*((Nsamples)^5)*(Nsamples+1)*(Nsamples+3)*(Nsamples+5)*(Nsamples+7))","v":1.7622488638026352E-6},{"$f":"((Nsamples-1)^9)*(($D$4)^5)/((FACT(5))*((Nsamples)^5)*(Nsamples+1)*(Nsamples+3)*(Nsamples+5)*(Nsamples+7))","v":1.7622488638026352E-6},null,"C",{"$f":"1/Nsamples-(($G$8^2/NORMSINV(0.95)^2)*((2*Nsamples-3)/(2*Nsamples-2)))","v":-0.5665427316302029}]
[null,"term 6",null,{"$f":"((Nsamples-1)^11)*(($D$4)^6)/((FACT(6))*((Nsamples)^6)*(Nsamples+1)*(Nsamples+3)*(Nsamples+5)*(Nsamples+7)*(Nsamples+9))","v":4.0045072491197995E-8}]
[null,"sum",{"$f":"SUM(C6:C11)","v":1.2591410050102765},{"$f":"SUM(D6:D12)","v":1.259141045055349},null,"B^2",{"$f":"$G$10^2","v":0.9361659260558147}]
[{"$nulls":5},"4AC",{"$f":"4*$G$9*$G$11","v":0.7536706003264882},{"$f":"H15+G14","v":0.9361659260558147}]
[null,"MVUE",{"$f":"EXP(MeanLogT)*SUM(C6:C11)","v":0.07353478365416219},{"$f":"EXP(MeanLogT)*SUM(D6:D12)","v":0.0735347859928246},null,"SQRT(B^2-4AC)",{"$f":"SQRT($G$13-$G$14)","v":0.4271947164108265},{"$f":"G15^2","v":0.18249532572932647}]
[{"$nulls":5},"2A",{"$f":"2*$G$9","v":-0.6651489448623168}]
[null,"MLE",{"$f":"EXP(MeanLogT+((StdLogT)^2)/2)","v":0.07502000844071018},{"$f":"EXP(MeanLogT)*EXP(D4)","v":0.07502000844071016},null,"U (UCL95%)",{"$f":"(-$G$10-$G$15)/$G$16","v":2.0969008605607247},{"$f":"(-$G$10+$G$15)/$G$16","v":0.8123924216297898}]
[{"$nulls":5},"PEP (UCL95%)",{"$f":"100*(1-NORMSDIST($G$17))","v":1.800117617447905},{"$f":"100*(1-NORMSDIST($H$17))","v":20.828324667873233}]

{"sheet":"UTL","index":10,"n_rows":56,"n_cols":12,"rows_kept":56,"hidden":true}
["Upper tolerance limit"]
[]
[null,"K Factor table"]
[null,"n","K\n(95, 95)","K\n(x, 95)",null,null,"UTL\nLognormal","n","UTL\nNormal"]
[null,3,7.655,{"$nulls":4},{"$f":"Nsamples","v":15}]
[null,4,5.145,null,null,"Mean (ln x)",{"$f":"MeanLogT","v":{"v":-2.8404264841302473,"d":"-2.840"}},null,{"$f":"Mean","v":{"v":0.0713,"d":"0.071"}},"Mean"]
[null,5,4.202,null,null,"SD (ln x)",{"$f":"StdLogT","v":{"v":0.7077090677879492,"d":"0.708"}},null,{"$f":"StdDev","v":{"v":0.0453,"d":"0.045"}},"SD"]
[null,6,3.707,{"$nulls":3},"K factor (95,95)",{"$f":"IF(Nsamples=\"\",\"\",VLOOKUP(Nsamples,KTable,2))","v":2.566},{"$nulls":3},"K factor (x,95)"]
[null,7,3.399,null,null,"UTL",{"$f":"IF(Nsamples=\"\",\"\",EXP(MeanLogT+(KFactor*StdLogT)))","v":0.3589956469027805},null,{"$f":"IF(Nsamples=\"\",\"\",Mean+(KFactor*StdDev))","v":0.18753979999999998},"UTL"]
[null,8,3.188]
[null,9,3.031]
[null,10,2.911]
[null,11,2.815]
[null,12,2.736]
[null,13,2.67]
[null,14,2.614]
[null,15,2.566]
[null,16,2.523]
[null,17,2.486]
[null,18,2.453]
[null,19,2.423]
[null,20,2.396]
[null,21,2.371]
[null,22,2.35]
[null,23,2.329]
[null,24,2.309]
[null,25,2.292]
[null,26,2.2776]
[null,27,2.2632]
[null,28,2.2488]
[null,29,2.2344]
[null,30,2.22]
[null,31,2.2092]
[null,32,2.1984]
[null,33,2.1876]
[null,34,2.1768]
[null,35,2.166]
[null,36,{"$f":"(($C$37-$C$42)/5)+C39","v":2.1578}]
[null,37,{"$f":"(($C$37-$C$42)/5)+C40","v":2.1496}]
[null,38,{"$f":"(($C$37-$C$42)/5)+C41","v":2.1414}]
[null,39,{"$f":"(($C$37-$C$42)/5)+C42","v":2.1332}]
[null,40,2.125]
[null,41,{"$f":"(($C$42-$C$47)/5)+C44","v":2.1184000000000007}]
[null,42,{"$f":"(($C$42-$C$47)/5)+C45","v":2.1118000000000006}]
[null,43,{"$f":"(($C$42-$C$47)/5)+C46","v":2.1052000000000004}]
[null,44,{"$f":"(($C$42-$C$47)/5)+C47","v":2.0986000000000002}]
[null,45,2.092]
[null,46,{"$f":"(($C$47-$C$52)/5)+C49","v":2.0865999999999993}]
[null,47,{"$f":"(($C$47-$C$52)/5)+C50","v":2.0811999999999995}]
[null,48,{"$f":"(($C$47-$C$52)/5)+C51","v":2.0757999999999996}]
[null,49,{"$f":"(($C$47-$C$52)/5)+C52","v":2.0704}]
[null,50,2.065]
[null,60,2.022]
[null,80,1.965]
[null,100,1.927]
[null,200,1.837]

{"sheet":"WTC","index":11,"n_rows":53,"n_cols":12,"rows_kept":53,"hidden":true}
[" W Test Calculated",{"$nulls":7},"Norm","Log Norm"]
[]
[{"$nulls":6},"i","ai","ai(xn-i+1-xi)","ai(LNxn-i+1-LN(xi)",{"$f":"term1(G14,H14,RangeData)","v":""}]
[null,"d=",{"$f":"(StdDev^2)*(Nsamples-1)","v":0.02872926},{"$nulls":3},{"$f":"1","v":1},{"$f":"IF(G4=\"\",\"\",HLOOKUP(G4,WTT_1,IF(Nsamples>50,50,Nsamples)))","v":0.515},{"$f":"term1(G4,H4,RangeData)","v":0.09785},{"$f":"term2(G4,H4,RangeData)","v":1.542802120880305},"",{"$f":"LOG(H4*8.8)","v":0.6562899011913598}]
[null,"k=",{"$f":"INT(Nsamples/2)","v":7},{"$nulls":3},{"$f":"IF(G4<kValue,G4+1,\"\")","v":2},0.3306,0.023142000000000003,0.39803340911015456,""]
[{"$nulls":6},{"$f":"IF(G5<kValue,G5+1,\"\")","v":3},0.2495,0.017465,0.3003912146793211,""]
[{"$nulls":4},"Accept Normal or Lognormal?",null,4,0.1878,9.389999999999999E-3,0.15229269460542647,""]
[null,"w=",{"$f":"IF(ISERROR(C12),\"\",C12^2/C4)","v":0.8702382840351618},{"$f":"HLOOKUP(0.05,WPtable,IF(Nsamples>50,49,Nsamples)-1)","v":0.881},{"$f":"IF(ISERROR(C12),\"\",IF(C8<D8,\"No\",\"Yes\"))","v":"No"},null,5,0.1353,0.006764999999999999,0.10971885825406923,""]
[null,"W (Ln Data)=",{"$f":"IF(ISERROR(D12),\"\",D12^2/((StdLogT^2)*(Nsamples-1)))","v":0.9324867465572501},{"$f":"HLOOKUP(0.05,WPtable,IF(Nsamples>50,49,Nsamples)-1)","v":0.881},{"$f":"IF(ISERROR(D12),\"\",IF(C9<D9,\"No\",\"Yes\"))","v":"Yes"},null,6,0.088,2.6399999999999996E-3,0.0413603193736247,""]
[{"$nulls":6},7,0.0433,8.6600000000000012E-4,0.012456633737162107,""]
[null,null,"normal","lognormal",null,null,"","","","",""]
[null,"Sum :",{"$f":"SUM(I4:I53)","v":0.15811800000000004},{"$f":"SUM(J4:J53)","v":2.557055250640063},null,null,"","","","",""]
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[{"$nulls":6},"","","","",""]
[{"$nulls":6},"","","","",""]
[{"$nulls":6},"","","","",""]
[{"$nulls":6},"","","","",""]
[{"$nulls":6},"","","","",""]
[{"$nulls":6},"","","","",""]
[{"$nulls":6},"","","","",""]
[{"$nulls":6},"","","","",""]
[{"$nulls":6},"","","","",""]
[{"$nulls":6},"","","","",""]
[{"$nulls":6},"","","","",""]
[{"$nulls":6},"","","","",""]
[{"$nulls":6},"","","","",""]
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[{"$nulls":6},"","","","",""]
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[{"$nulls":6},"","","","",""]
[{"$nulls":6},"","","","",""]
[{"$nulls":6},"","","","",""]
[{"$nulls":6},"","","","",""]
[{"$nulls":6},"","","","",""]
[{"$nulls":6},"",{"$f":"IF(G36=\"\",\"\",HLOOKUP(G36,WTT_1,IF(Nsamples>50,50,Nsamples)))","v":""},{"$f":"term1(G36,H36,RangeData)","v":""},{"$f":"term2(G36,H36,RangeData)","v":""},""]
[{"$nulls":6},"","","","",""]
[{"$nulls":6},"","","","",""]
[{"$nulls":6},"","","","",""]
[{"$nulls":6},"","","","",""]
[{"$nulls":6},"","","","",""]
[{"$nulls":6},"","","","",""]
[{"$nulls":6},"","","",""]
[{"$nulls":6},"","","",""]
[{"$nulls":6},"","","",""]
[{"$nulls":6},"","","",""]
[{"$nulls":6},"","","",""]
[{"$nulls":6},"","","",""]
[{"$nulls":6},"","","",""]
[{"$nulls":6},"","","",""]
[{"$nulls":6},"","","",""]
[{"$nulls":6},"","","",""]
[{"$nulls":6},"","","",""]

{"sheet":"WPC","index":12,"n_rows":52,"n_cols":8,"rows_kept":52,"hidden":true}
[null,null,"W Percentage Table"]
[]
[{"$nulls":3},"W α"]
[{"$nulls":3},{"v":0.01,"d":"1%"},{"v":0.02,"d":"2%"},{"v":0.05,"d":"5%"},{"v":0.1,"d":"10%"},{"v":0.5,"d":"50%"}]
[null,"n",3,0.753,0.756,0.767,0.789,0.959]
[null,null,4,0.687,0.707,0.748,0.792,0.935]
[null,null,5,0.686,0.715,0.762,0.806,0.927]
[null,null,6,0.713,0.743,0.788,0.826,0.927]
[null,null,7,0.73,0.76,0.803,0.838,0.928]
[null,null,8,0.749,0.778,0.818,0.851,0.932]
[null,null,9,0.764,0.791,0.829,0.859,0.935]
[null,null,10,0.781,0.806,0.842,0.869,0.938]
[null,null,11,0.792,0.817,0.85,0.876,0.94]
[null,null,12,0.805,0.828,0.859,0.883,0.943]
[null,null,13,0.814,0.837,0.866,0.889,0.945]
[null,null,14,0.825,0.846,0.874,0.895,0.947]
[null,null,15,0.835,0.855,0.881,0.901,0.95]
[null,null,16,0.844,0.863,0.887,0.906,0.952]
[null,null,17,0.851,0.869,0.892,0.91,0.954]
[null,null,18,0.858,0.874,0.897,0.914,0.956]
[null,null,19,0.863,0.879,0.901,0.917,0.957]
[null,null,20,0.868,0.884,0.905,0.92,0.959]
[null,null,21,0.873,0.888,0.908,0.923,0.96]
[null,null,22,0.878,0.892,0.911,0.926,0.961]
[null,null,23,0.881,0.895,0.914,0.928,0.962]
[null,null,24,0.884,0.898,0.916,0.93,0.963]
[null,null,25,0.886,0.901,0.918,0.931,0.964]
[null,null,26,0.891,0.904,0.92,0.933,0.965]
[null,null,27,0.894,0.906,0.923,0.935,0.965]
[null,null,28,0.896,0.908,0.924,0.936,0.966]
[null,null,29,0.898,0.91,0.926,0.937,0.966]
[null,null,30,0.9,0.912,0.927,0.939,0.967]
[null,null,31,0.902,0.914,0.929,0.94,0.967]
[null,null,32,0.904,0.915,0.93,0.941,0.968]
[null,null,33,0.906,0.917,0.931,0.942,0.968]
[null,null,34,0.908,0.919,0.933,0.943,0.969]
[null,null,35,0.91,0.92,0.934,0.944,0.969]
[null,null,36,0.912,0.922,0.935,0.945,0.97]
[null,null,37,0.914,0.924,0.936,0.946,0.97]
[null,null,38,0.916,0.925,0.938,0.947,0.971]
[null,null,39,0.917,0.927,0.939,0.948,0.971]
[null,null,40,0.919,0.928,0.94,0.949,0.972]
[null,null,41,0.92,0.929,0.941,0.95,0.972]
[null,null,42,0.922,0.93,0.942,0.951,0.972]
[null,null,43,0.923,0.932,0.943,0.951,0.973]
[null,null,44,0.924,0.933,0.944,0.952,0.973]
[null,null,45,0.926,0.934,0.945,0.953,0.973]
[null,null,46,0.927,0.935,0.945,0.953,0.974]
[null,null,47,0.928,0.936,0.946,0.954,0.974]
[null,null,48,0.929,0.937,0.947,0.954,0.974]
[null,null,49,0.929,0.937,0.947,0.955,0.974]
[null,null,50,0.93,0.938,0.947,0.955,0.974]

{"sheet":"WTT","index":13,"n_rows":51,"n_cols":29,"rows_kept":51,"hidden":true}
[null,null,"W Test Table"]
[null,null,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,null,"Sum"]
[null,2,0.7071,{"$nulls":25},{"$f":"SUM(C3:AA3)","v":0.7071}]
[null,3,0.7071,0,{"$nulls":24},0.7071]
[null,4,0.6872,0.1677,{"$nulls":24},0.8549]
[null,5,0.6646,0.2413,0,{"$nulls":23},0.9058999999999999]
[null,6,0.6431,0.2896,0.0875,{"$nulls":23},1.0202]
[null,7,0.6233,0.3031,0.1401,0,{"$nulls":22},1.0665]
[null,8,0.6052,0.3164,0.1743,0.0561,{"$nulls":22},1.152]
[null,9,0.5888,0.3244,0.1976,0.0947,0,{"$nulls":21},1.2055]
[null,10,0.5739,0.3291,0.2141,0.1224,0.0399,{"$nulls":21},1.2794]
[null,11,0.5601,0.3315,0.226,0.1429,0.0695,0,{"$nulls":20},1.33]
[null,12,0.5475,0.3325,0.2347,0.1586,0.0922,0.0303,{"$nulls":20},1.3958000000000002]
[null,13,0.5359,0.3325,0.2412,0.1707,0.1099,0.0539,0,{"$nulls":19},1.4441000000000002]
[null,14,0.5251,0.3318,0.246,0.1802,0.124,0.0727,0.024,{"$nulls":19},1.5037999999999998]
[null,15,0.515,0.3306,0.2495,0.1878,0.1353,0.088,0.0433,0,{"$nulls":18},1.5494999999999999]
[null,16,0.5056,0.329,0.2521,0.1939,0.1447,0.1005,0.0593,0.0196,{"$nulls":18},1.6047]
[null,17,0.4968,0.3273,0.254,0.1988,0.1524,0.1109,0.0725,0.0359,0,{"$nulls":17},1.6486000000000003]
[null,18,0.4886,0.3253,0.2553,0.2027,0.1587,0.1197,0.0837,0.0496,0.0163,{"$nulls":17},1.6999]
[null,19,0.4808,0.3232,0.2561,0.2059,0.1641,0.1271,0.0932,0.0612,0.0303,0,{"$nulls":16},1.7418999999999998]
[null,20,0.4734,0.3211,0.2565,0.2085,0.1686,0.1334,0.1013,0.0711,0.0422,0.014,{"$nulls":16},1.7900999999999998]
[null,21,0.4643,0.3185,0.2578,0.2119,0.1736,0.1399,0.1092,0.0804,0.053,0.0263,0,{"$nulls":15},1.8348999999999998]
[null,22,0.459,0.3156,0.2571,0.2131,0.1764,0.1443,0.115,0.0878,0.0618,0.0368,0.0122,{"$nulls":15},1.8791]
[null,23,0.4542,0.3126,0.2563,0.2139,0.1787,0.148,0.1201,0.0941,0.0696,0.0459,0.0228,0,{"$nulls":14},1.9162000000000001]
[null,24,0.4493,0.3098,0.2554,0.2145,0.1807,0.1512,0.1245,0.0997,0.0764,0.0539,0.0321,0.0107,{"$nulls":14},1.9582]
[null,25,0.445,0.3069,0.2543,0.2148,0.1822,0.1539,0.1283,0.1046,0.0823,0.061,0.0403,0.02,0,{"$nulls":13},1.9936]
[null,26,0.4407,0.3043,0.2533,0.2151,0.1836,0.1563,0.1316,0.1089,0.0876,0.0672,0.0476,0.0284,0.0094,{"$nulls":13},2.034]
[null,27,0.4366,0.3018,0.2522,0.2152,0.1848,0.1584,0.1346,0.1128,0.0923,0.0728,0.054,0.0358,0.0178,0,{"$nulls":12},2.0691]
[null,28,0.4328,0.2992,0.251,0.2151,0.1857,0.1601,0.1372,0.1162,0.0965,0.0778,0.0598,0.0424,0.0253,0.0084,{"$nulls":12},2.1075000000000004]
[null,29,0.4291,0.2968,0.2499,0.215,0.1864,0.1616,0.1395,0.1192,0.1002,0.0822,0.065,0.0483,0.032,0.0159,0,{"$nulls":11},2.1411]
[null,30,0.4254,0.2944,0.2487,0.2148,0.187,0.163,0.1415,0.1219,0.1036,0.0862,0.0697,0.0537,0.0381,0.0227,7.6E-3,{"$nulls":11},2.1783]
[null,31,0.422,0.2921,0.2475,0.2145,0.1874,0.1641,0.1433,0.1243,0.1066,0.0899,0.0739,0.0585,0.0435,0.0289,0.0144,0,{"$nulls":10},2.2109]
[null,32,0.4188,0.2898,0.2462,0.2141,0.1878,0.1651,0.1449,0.1265,0.1093,0.0931,0.0777,0.0629,0.0485,0.0344,0.0206,0.0068,{"$nulls":10},2.2465000000000006]
[null,33,0.4156,0.2876,0.2451,0.2137,0.188,0.166,0.1463,0.1284,0.1116,0.0961,0.0812,0.0669,0.053,0.0395,0.0262,0.0131,0,{"$nulls":9},2.2783]
[null,34,0.4127,0.2854,0.2439,0.2132,0.1882,0.1667,0.1475,0.1301,0.114,0.0988,0.0844,0.0706,0.0572,0.0441,0.0314,0.0187,0.0062,{"$nulls":9},{"$f":"SUM(C35:AA35)","v":2.3131}]
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