Bayesian t-Test Teaching App

Preliminary Version

The goal of the Bayesian t-test app is to provide teachers with a handy tool to show students what a Bayes factor, and more generally, what the results from a Bayesian t-test look like when data points are added in real-time.

References

  1. Ly, A., Verhagen, A. J., & Wagenmakers, E.-J. (2016). Harold Jeffreys's default Bayes factor hypothesis tests: Explanation, extension, and application in psychology. Journal of Mathematical Psychology, 72, 19-32. http://dx.doi.org.sci-hub.cc/10.1016/j.jmp.2015.06.004
  2. Rouder, J. N., Speckman, P. L., Sun, D., Morey, R. D., & Iverson, G. (2009). Bayesian t tests for accepting and rejecting the null hypothesis. Psychonomic Bulletin & Review, 16, 225-237. http://sci-hub.cc/10.3758/PBR.16.2.225
  3. 3. Wetzels, R., Raaijmakers, J. G. W., Jakab, E., & Wagenmakers, E.-J. (2009). How to quantify support for and against the null hypothesis: A Bayesian t test. Psychonomic Bulletin & Review, 16, 752-760. http://sci-hub.cc/10.3758/PBR.16.4.752


TquanT was co-funded by the Erasmus+ Programme of the European Commission.

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© 2016, Tara Cohen & E.J. Wagenmakers, University of Amsterdam, The Netherlands

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