<i>Stop and Think About p-Value Statistics: Fisher, Neyman, and E. Pearson Revisited</i>
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- MORIMOTO Ryota
- Health Sciences University of Hokkaido
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説明
<p> Good statistical practice is an integral part of modern science. Null hypothesis significance testing (NHST) is the most widely used statistical method. Nevertheless, misuse and misinterpretation of NHST are widespread, and severe criticisms have been levelled against NHST. In this study, I revisit the primary documents of Fisher, Neyman, and E. Pearson relating to statistical testing. I compare Fisher’s significance testing with Neyman-Pearson hypothesis testing and clarify their thoughts on statistical testing. I hope this study will guide researchers in stopping and thinking about p-value statistics before abandoning it.</p>
収録刊行物
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- Ａｎｎａｌｓ ｏｆ ｔｈｅ Ｊａｐａｎ Ａｓｓｏｃｉａｔｉｏｎ ｆｏｒ Ｐｈｉｌｏｓｏｐｈｙ ｏｆ Ｓｃｉｅｎｃｅ
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Ａｎｎａｌｓ ｏｆ ｔｈｅ Ｊａｐａｎ Ａｓｓｏｃｉａｔｉｏｎ ｆｏｒ Ｐｈｉｌｏｓｏｐｈｙ ｏｆ Ｓｃｉｅｎｃｅ 30 (0), 43-65, 2021
科学基礎論学会
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詳細情報 詳細情報について
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- CRID
- 1390571859153339776
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- NII論文ID
- 130008128854
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- ISSN
- 18841228
- 04530691
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- 本文言語コード
- en
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- 資料種別
- journal article
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- データソース種別
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- JaLC
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- OpenAIRE
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