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V洗浴
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审问
发表于 2025-3-22 00:25:59
Holger Schramm,Benedikt Spangardt,Nicolas Ruth combining .P.-values that arise from small data sets, multiple dichotomous response analyses, problems regarding Fisher’s Z transformation for correlation analyses, and multivariate similarity comparisons between corresponding multiple categories of two samples.
性满足
发表于 2025-3-22 08:24:18
Holger Schramm,Benedikt Spangardt,Nicolas Ruths may not be aware of the fundamental lemma of Neyman and Pearson, but they know that the statistic they wanttouse—acomplexscoreoraratioofscores,doesnothaveanalready well-tabulated distribution. 2. Pressure from regulatory agencies for the use of methods that yield exact signi?cance levels, not appr
Ophthalmologist
发表于 2025-3-22 11:35:02
s may not be aware of the fundamental lemma of Neyman and Pearson, but they know that the statistic they wanttouse—acomplexscoreoraratioofscores,doesnothaveanalready well-tabulated distribution. 2. Pressure from regulatory agencies for the use of methods that yield exact signi?cance levels, not appr
夸张
发表于 2025-3-22 15:22:58
Holger Schramm,Benedikt Spangardt,Nicolas Ruthstatistic they wanttouse—acomplexscoreoraratioofscores,doesnothaveanalready well-tabulated distribution. 2. Pressure from regulatory agencies for the use of methods that yield exact signi?cance levels, not appr978-1-4419-1907-6978-0-387-27158-3Series ISSN 0172-7397 Series E-ISSN 2197-568X
conscience
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circuit
发表于 2025-3-22 22:00:08
Holger Schramm,Benedikt Spangardt,Nicolas Ruthstatistic they wanttouse—acomplexscoreoraratioofscores,doesnothaveanalready well-tabulated distribution. 2. Pressure from regulatory agencies for the use of methods that yield exact signi?cance levels, not appr978-1-4419-1907-6978-0-387-27158-3Series ISSN 0172-7397 Series E-ISSN 2197-568X
离开真充足
发表于 2025-3-23 02:33:53
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盲信者
发表于 2025-3-23 08:16:51
Holger Schramm,Benedikt Spangardt,Nicolas Ruthg .P.-values that arise from small data sets, multiple dichotomous response analyses, problems regarding Fisher’s Z transformation for correlation analyses, and multivariate similarity comparisons between corresponding multiple categories of two samples.978-1-4419-2416-2978-0-387-69813-7Series ISSN 0172-7397 Series E-ISSN 2197-568X