How do I calculate effect sizes for different statistical tests?

How do I calculate effect sizes for different statistical tests?

Effect size measures the strength of a phenomenon. For t-tests, you can use Cohen's d, while for ANOVA, you might use eta squared.

Can you explain Cohen's d and how to interpret it?

Cohen's d is the difference between two means divided by the pooled standard deviation. A d of 0.2 is small, 0.5 is medium, and 0.8 is large.

What about effect sizes for regression analysis?

For regression, you can use R-squared, which indicates the proportion of variance explained by the model. Higher values mean a better fit.

Are there any guidelines for reporting effect sizes?

Yes, it's important to report the effect size along with the p-value to provide context for the statistical significance.