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{"title":"Non-Parametric Comparison of Single Parameter Histograms","authors":"James C.S. Wood","doi":"10.1002/cpcy.33","DOIUrl":null,"url":null,"abstract":"<p>A number of methods have been developed to compare single parameter histograms. Some perform a channel-by-channel analysis and others give a single statistic about how the histograms may or may not differ. If they do differ, then the significance of the difference or confidence limit is usually provided. The specific location(s) for the greatest deviations may also be given. Some are more effective at resolving severely overlapping populations and others work poorly when there is any significant overlap. Each method makes certain assumptions about the data. It is important to understand the assumptions being made and to understand the limitations of each method. It is essential to know how to identify when a comparison method will work for a given set of histograms. This unit explores the different methods, and provides a guide for the reader to choose the most appropriate method(s) to use for a specific data set(s). © 2018 by John Wiley & Sons, Inc.</p>","PeriodicalId":11020,"journal":{"name":"Current Protocols in Cytometry","volume":"83 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/cpcy.33","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Protocols in Cytometry","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cpcy.33","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Health Professions","Score":null,"Total":0}
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Abstract
A number of methods have been developed to compare single parameter histograms. Some perform a channel-by-channel analysis and others give a single statistic about how the histograms may or may not differ. If they do differ, then the significance of the difference or confidence limit is usually provided. The specific location(s) for the greatest deviations may also be given. Some are more effective at resolving severely overlapping populations and others work poorly when there is any significant overlap. Each method makes certain assumptions about the data. It is important to understand the assumptions being made and to understand the limitations of each method. It is essential to know how to identify when a comparison method will work for a given set of histograms. This unit explores the different methods, and provides a guide for the reader to choose the most appropriate method(s) to use for a specific data set(s). © 2018 by John Wiley & Sons, Inc.
单参数直方图的非参数比较
已经开发了许多方法来比较单参数直方图。一些执行逐个通道的分析,另一些给出关于直方图可能或可能没有差异的单一统计。如果它们确实不同,那么通常会提供差异的显著性或置信限。还可以给出最大偏差的具体位置。有些方法在解决严重重叠的人群时更有效,而另一些方法在存在重大重叠时效果不佳。每种方法对数据都有一定的假设。理解所做的假设和理解每种方法的局限性是很重要的。了解如何确定比较方法何时适用于给定的直方图集是至关重要的。本单元探讨了不同的方法,并为读者提供了一个指南,以选择最合适的方法来使用特定的数据集。©2018 by John Wiley &儿子,Inc。
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