What is the difference between effect size and p-value?
An example of an AI chatbot conversation about effect size and p-value in statistics.
What is the difference between effect size and p-value?
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.
Can you give me an example of effect size?
Sure! In a study comparing two groups, if the mean difference in scores is 5 and the standard deviation is 10, the effect size (Cohen's d) would be 0.5, indicating a medium effect.
How do I interpret a p-value?
A p-value tells you the likelihood of obtaining your results under the null hypothesis. A p-value less than 0.05 typically indicates statistical significance.
Which one is more important in research?
Both are important! Effect size provides context on the practical significance, while p-value helps assess statistical significance.
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