What are confidence intervals in A/B testing?
Confidence intervals in A/B testing provide a range of values that likely contain the true effect of a change, helping to assess the reliability of the results.
How do I calculate a confidence interval for my A/B test results?
To calculate a confidence interval, you typically use the formula: CI = mean ± (Z * (standard deviation / √n)), where Z is the Z-score for your desired confidence level.
What does a 95% confidence interval mean?
A 95% confidence interval means that if you were to conduct the same A/B test multiple times, 95% of the calculated intervals would contain the true effect size.
Can you give an example of interpreting a confidence interval?
Sure! If your A/B test results in a 95% confidence interval of [2%, 5%], you can say that you are 95% confident that the true effect of the change lies between 2% and 5%.
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