Persistent Confusions about Hypothesis Testing in the Social Sciences

Christopher Thron and Vincent Miller
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Christopher Thron: Department of Mathematics, Texas A&M University-Central Texas, 1001 Leadership Place, Killeen, TX 76549, USA
Vincent Miller: Department of Mathematics, Texas A&M University-Central Texas, 1001 Leadership Place, Killeen, TX 76549, USA

Social Sciences, 2015, vol. 4, issue 2, 1-12

Abstract: This paper analyzes common confusions involving basic concepts in statistical hypothesis testing. One-third of the social science statistics textbooks examined in the study contained false statements about significance level and/or p -value. We infer that a large proportion of social scientists are being miseducated about these concepts. We analyze the causes of these persistent misunderstandings, and conclude that the conventional terminology is prone to abuse because it does not clearly represent the conditional nature of probabilities and events involved. We argue that modifications in terminology, as well as the explicit introduction of conditional probability concepts and notation into the statistics curriculum in the social sciences, are necessary to prevent the persistence of these errors.

Keywords: statistics; hypothesis testing; inference; p -value; significance; conditional probability; conditional event (search for similar items in EconPapers)
JEL-codes: A B N P Y80 Z00 (search for similar items in EconPapers)
Date: 2015
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