What is effect size and how do I interpret it?
An example of an AI chatbot conversation about interpreting effect size in statistics.
What is effect size and how do I interpret it?
Effect size is a quantitative measure of the magnitude of a phenomenon. It helps to understand the strength of a relationship or the size of a difference.
Can you give me an example of effect size?
Sure! For instance, in a study comparing two groups, if the mean difference in scores is 10 and the standard deviation is 5, the effect size (Cohen's d) would be 2.0, indicating a large effect.
How do I know if an effect size is considered small, medium, or large?
Cohen suggested that an effect size of 0.2 is small, 0.5 is medium, and 0.8 is large. However, context matters!
What are some common types of effect size measures?
Common measures include Cohen's d, Pearson's r, and odds ratios. Each serves different types of data and research designs.
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