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Simpson's paradox, or the Yule–Simpson effect, is a paradox in probability and statistics, in which a trend appears in different groups of data but disappears or reverses when these groups are combined. It is sometimes given the impersonal title reversal paradox or amalgamation paradox. This result is often encountered in social-science and medical-science statistics, and is particularly confounding when frequency data are unduly given causal interpretations.〔Judea Pearl. ''Causality: Models, Reasoning, and Inference'', Cambridge University Press (2000, 2nd edition 2009). ISBN 0-521-77362-8.〕 Simpson's paradox disappears when causal relations are brought into consideration. Many statisticians believe that the mainstream public should be informed of the counter-intuitive results in statistics such as Simpson's paradox.〔Robert L. Wardrop (February 1995). "Simpson's Paradox and the Hot Hand in Basketball". ''The American Statistician'', 49 (1): pp. 24–28.〕〔Alan Agresti (2002). "Categorical Data Analysis" (Second edition). John Wiley and Sons ISBN 0-471-36093-7〕 Edward H. Simpson first described this phenomenon in a technical paper in 1951, but the statisticians Karl Pearson, et al., in 1899,〔 〕 and Udny Yule, in 1903, had mentioned similar effects earlier. The name ''Simpson's paradox'' was introduced by Colin R. Blyth in 1972. ==Examples== 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Simpson's paradox」の詳細全文を読む スポンサード リンク
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