# Standardized effect sizes

CogStat calculates various standardized effect sizes.

- The effect sizes are differentiated as sample effect sizes and population effect size estimations in the results. (This distinction is not obvious in many textbooks or methodological works.)
- For a single effect, there might be several effect sizes, because they might reflect different aspects of the effect.
- When appropriate, confidence intervals of the population estimations are also provided.
- You might mainly use these effect sizes to describe the effect you investigate, but these effect sizes are also useful in evaluating the power of the hypothesis tests.
- Only standardized effect sizes are calculated, but not unstandardized effect sizes, because usually the latter ones can be calculated easily (e.g., the difference of the group means).

Explore relation of a variable pair:

- Pearson correlation coefficient and its confidence interval
- Spearman correlation coefficient and its confidence interval
- Cramér’s V

Compare repeated measures variables:

- Cohen’s d
- Eta-squared
- Hedges’ g and its confidence interval

- Cohen’s d
- Eta-squared
- Hedges’ g and its confidence interval
- Omega-squared
- Cramér’s V