Articles exploring false positives through the lens of behavioral science and experimentation. Practical frameworks for growth leaders who measure in revenue, not vanity metrics.
3 articles
Checking A/B test results before the planned endpoint is the most common validity threat in experimentation. Learn why it happens and how to prevent it.
Regression to the mean explains why early A/B test results often look dramatic but fade over time. Learn why patience in experimentation prevents costly false conclusions.
Why false positives are the biggest threat to A/B testing programs, how A/A tests prove the problem is real, and why stopping at significance is the number one mistake teams make.