Required Sample Size
Enter your parameters and click Calculate to see the required sample size
Understanding Type I and Type II Errors
Type I Error (False Positive)
Occurs when you reject the null hypothesis when it's actually true. You detect an effect that isn't really there. Controlled by the significance level (α), typically set at 5%.
Type II Error (False Negative)
Occurs when you fail to reject the null hypothesis when it's actually false. You miss detecting a real effect. Controlled by statistical power (1 - β), typically set at 80%.
Common Questions
What is Baseline Conversion Rate?
The expected conversion rate of your control group without any changes.
What is Minimum Detectable Effect?
The smallest change in conversion rate that you want to detect, expressed as a percentage increase or decrease from the baseline.
Why is Statistical Significance important?
It helps you determine the likelihood that your results are due to the changes made and not by random chance.
What does Statistical Power tell us?
It indicates the probability that your test will detect a true effect when there is one.
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