Relationship between your variables

1. Think about the variables in your study. Find at least two articles you have read that report the effect size of the relationship between your variables (this could be Pearson r for a correlation or Eta squared for ANOVA, Cohen’s d for a t-test, etc.). Use those effect sizes to determine the number of participants needed in your study to have enough power to detect your effect (where Power = 80%).

2. Will you need more, or fewer, participants than other students? Briefly, why (be sure to mention the main aspects of study relationships that influence power using the resources above – variability, N, strength of effect size)? Power Calculator – choose your test. Link – https://statpages.info/#Power.

3. Talk to your instructor if you aren’t sure what test to use (but try to figure it out on your own first using the flow chart about hypothesis tests in Module 1). These tests will ask for an estimate of the population (regular, everyday/no experimental treatment) mean and SD. I would look these up in a study examining your variable that uses a control group). G*Power is easier, but does not always work for Macintosh.

If you do not see your hypothesis test above, please click on THIS LINK. https://www.surveysystem.com/sscalc.htm