Hypothesis testing
Content for Friday, September 9, 2022
Content
- Sampling variability
- Hypothesis testing
- Pairwise comparisons
Learning objectives
At the end of the session, students should be capable of
- understanding the mechanics behind generic hypothesis tests
- interpreting the output of generic tests
- correctly reporting the output of a testing procedure
Readings
- Chapter 5 (Foundations for inference) of Matthew Crump’s course notes. These notes are non-technical, but do a good job at explaining the notion of sampling variability and chance. If you find them too basic, skip directly to the next item.
- Chapter 2 of the Course notes
- The permutation test by Jared Wilson
Complementary readings
- Chapter 3 of Keppel & Wickens (2004).
Slides
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Tip
Fun fact: If you type ? (or shift + /) while going through the slides, you can see a list of slide-specific commands.
Case study
We will look at the way authors report the conclusion of their statistical tests with
References
Brucks, M. S., & Levav, J. (2022). Virtual communication curbs creative idea generation. Nature, 605(7908), 108–112. https://doi.org/10.1038/s41586-022-04643-y
Keppel, G., & Wickens, T. D. (2004). Design and analysis: A researcher’s handbook. Pearson Prentice Hall.
Liu, P. J., Rim, S., Min, L., & Min, K. E. (2022+). The surprise of reaching out: Appreciated more than we think. Journal of Personality and Social Psychology. https://doi.org/10.1037/pspi0000402
Rosen, B., & Jerdee, T. H. (1974). Influence of sex role stereotypes on personnel decisions. Journal of Applied Psychology, 59, 9–14. https://doi.org/10.1037/h0035834