What is the difference between effect size and confidence intervals?
An example of an AI chatbot conversation about effect size and confidence intervals in statistics.
What is the difference between effect size and confidence intervals?
Effect size measures the strength of a relationship or the magnitude of an effect, while confidence intervals provide a range of values that likely contain the true parameter.
Can you give me an example of effect size?
Sure! In a clinical trial, if a new drug reduces symptoms by an average of 5 points on a scale of 0-100, the effect size quantifies how significant that reduction is.
How do confidence intervals relate to effect size?
Confidence intervals help to understand the precision of the effect size estimate. A narrow interval suggests a more precise estimate, while a wide interval indicates more uncertainty.
Why are both important in research?
Both are crucial because effect size tells us about the practical significance of results, while confidence intervals inform us about the reliability of those results.
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