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When explaining a Pearson’s r, according to Cohen’s conventions a:
Small effect is about
Medium effect is about
Large effect is about
When explaining a Pearson’s correlation (r), according to Adam an effect size of:
> and < is considered small
> and < is considered medium
> is considered large
When explaining variance explained for either r² or η² a:
After running a one-way, between groups ANOVA, you find a η² variance of 0.2. What would be the ƒ² variance explained be?
What will increase the power of a study?
(mark all that apply)
Effect sizes are measures of the:
(mark all that are true)
Effect sizes are independent of sample size.
When using Cohen’s d, according to Cohen a:
Small effect is about
Medium effect is about
Large effect is about
When using Cohen’s d, according to Adam a: