What are the different effect size measures in statistics?
An example of an AI chatbot conversation about different effect size measures in statistics.
What are the different effect size measures in statistics?
Effect size measures quantify the strength of a relationship or the magnitude of an effect. Common types include Cohen's d, Pearson's r, and odds ratios.
Can you explain Cohen's d in more detail?
Cohen's d measures the difference between two means in terms of standard deviation. It's calculated as the difference between the group means divided by the pooled standard deviation.
What about Pearson's r? How is it different?
Pearson's r measures the strength and direction of a linear relationship between two continuous variables, ranging from -1 to 1.
Are there any other effect size measures I should know about?
Yes, other measures include odds ratios for binary outcomes and eta-squared for ANOVA, each serving different types of data.
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