What is the difference between effect size and p-value?
An example of an AI chatbot conversation about effect size and p-value differences.
Can you explain the difference between effect size and p-value?
Sure! Effect size measures the strength of a relationship or the magnitude of an effect, while p-value indicates the probability of observing the data if the null hypothesis is true.
Why is effect size important in research?
Effect size provides context to the significance of results, helping researchers understand the practical implications of their findings.
Can you give an example of effect size?
Absolutely! For instance, in a study comparing two teaching methods, an effect size of 0.5 might indicate a moderate difference in student performance between the two methods.
How do I calculate effect size?
Effect size can be calculated using various formulas, depending on the type of data. Common methods include Cohen's d for comparing two means and Pearson's r for correlation.
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