What is effect size and why is it important in research?
An example of an AI chatbot conversation about effect size in research and its practical implications.
What is effect size and why is it important in research?
Effect size is a quantitative measure of the magnitude of a phenomenon. It's important because it helps researchers understand the practical significance of their findings, beyond just statistical significance.
Can you give me an example of how effect size is used in a study?
Sure! In a clinical trial comparing two medications, the effect size can show how much more effective one medication is over the other, helping to inform treatment decisions.
How do I calculate effect size?
Effect size can be calculated using various methods, such as Cohen's d for comparing two means or Pearson's r for correlation. The choice depends on your data type.
What are the common types of effect size?
Common types include Cohen's d, which measures the difference between two means, and eta-squared, which assesses the proportion of variance explained by a factor.
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