Why should an A/B test not be stopped as soon as it shows a significant result?
- A Peeking and stopping early produces false positives at a much higher rate than the stated threshold
- B It is against platform rules
- C It costs more
- D The data is deleted
Answer
Peeking and stopping early produces false positives at a much higher rate than the stated threshold
Sample size should be calculated in advance from the baseline rate and the effect size worth detecting.





