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A response to White and Gorard: Against inferential statistics: How and why current statistics teaching gets it wrong

Nicholson, J.; Ridgway, J.

A response to White and Gorard: Against inferential statistics: How and why current statistics teaching gets it wrong Thumbnail


Authors

J. Nicholson



Abstract

White and Gorard make important and relevant criticisms of some of the methods commonly used in social science research, but go further by criticising the logical basis for inferential statistical tests. This paper comments briefly on matters we broadly agree on with them and more fully on matters where we disagree. We agree that too little attention is paid to the assumptions underlying inferential statistical tests, to the design of studies, and that p-values are often misinterpreted. We show why we believe their argument concerning the logic of inferential statistical tests is flawed, and how White and Gorard misrepresent the protocols of inferential statistical tests, and make brief suggestions for rebalancing the statistics curriculum.

Citation

Nicholson, J., & Ridgway, J. (2017). A response to White and Gorard: Against inferential statistics: How and why current statistics teaching gets it wrong. Statistics Education Research Journal, 16(1), 66-73

Journal Article Type Article
Acceptance Date Mar 1, 2017
Online Publication Date May 1, 2017
Publication Date May 1, 2017
Deposit Date Jul 20, 2017
Publicly Available Date Jul 31, 2017
Journal Statistics Education Research Journal
Publisher International Association for Statistics Education (IASE)
Peer Reviewed Peer Reviewed
Volume 16
Issue 1
Pages 66-73
Publisher URL https://iase-web.org/documents/SERJ/SERJ16(1)_Nicholson.pdf

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Published Journal Article (641 Kb)
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Copyright Statement
© International Association for Statistical Education (IASE/ISI)







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