The Bayesian two-sample t test

Mithat Gönen, Wesley O. Johnson, Yonggang Lu, Peter H. Westfall

Research output: Contribution to journalArticlepeer-review

66 Scopus citations

Abstract

This article shows how the pooled-variance two-sample t statistic arises from a Bayesian formulation of the two-sided point null testing problem, with emphasis on teaching. We identify a reasonable and useful prior giving a closed-form Bayes factor that can be written in terms of the distribution of the two-sample t statistic under the null and alternative hypotheses, respectively. This provides a Bayesian motivation for the two-sample t statistic, which has heretofore been buried as a special case of more complex linear models, or given only roughly via analytic or Monte Carlo approximations. The resulting formulation of the Bayesian test is easy to apply in practice, and also easy to teach in an introductory course that emphasizes Bayesian methods. The priors are easy to use and simple to elicit, and the posterior probabilities are easily computed using available software, in some cases using spreadsheets.

Original languageEnglish
Pages (from-to)252-257
Number of pages6
JournalAmerican Statistician
Volume59
Issue number3
DOIs
StatePublished - Aug 2005

Keywords

  • Bayes factor
  • Posterior probability
  • Prior elicitation
  • Teaching Bayesian statistics

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