1. One-Way BG ANOVA Andrew Ainsworth Psy 420 Obtained from www.csun.edu/~ata20315/psy420/One- Way%20BG%20ANOVA.ppt

2. Effect Size A significant effect depends: Size of the mean differences (effect) Size of the error variance Degrees of freedom Practical Significance Is the effect useful? Meaningful? Does the effect have any real utility?

3. Effect Size Raw Effect size – Just looking at the raw difference between the groups Can be illustrated as the largest group difference or smallest (depending) Can’t be compared across samples or experiments

4. Effect Size Standardized Effect Size Expresses raw mean differences in standard deviation units Usually referred to as Cohen’s d

5. Effect Size Standardized Effect Size Cohen established effect size categories.2 = small effect.5 = moderate effect.8 = large effect

6. Effect Size Percent of Overlap There are many effect size measures that indicate the amount of total variance that is accounted for by the effect

7. Effect Size Percent of Overlap Eta Squared simply a descriptive statistic Often overestimates the degree of overlap in the population

8. Effect Size Omega Squared This is a better estimate of the percent of overlap in the population Corrects for the size of error and the number of groups

9. Our Example EPRS8540 Eta Squared Small.01 Medium.06 Large.14 Cohen (1977) Omega Squared Small <.06 Medium.06 -.15 Large >.15 Cohen (1977)

10. Our Example EPRS8540 There was no significant price difference among the three store types (F 2, 9 = 3.12, P >.05, ).

11. References Cohen, J. (1977). Statistical power analysis for the behavioral sciences. NY: Academic Press. Cited with regard to intepretation of omega-square. Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Second ed., Hillsdale, NJ: Erlbaum. Olejnik, S., & Algina, J. (2003). Generalized eta and omega statistics: Measured for effect size for some common research designs, Psychological Methods, 8, 434 – 447.