8 articles in this category
Most A/B testing case studies are just survivorship bias in a nice suit. Here's why we stopped trusting them and what we do instead.
Most A/B test wins are false positives. Learn why peeking, low power, and ignoring practical significance inflate your results—and how to run tests th...
Peeking at your A/B test inflates false positives to 30%. Pre-commit to a sample size or use sequential testing to get trustworthy results.
Learn why peeking at your A/B test inflates false positives, and how to use pre-committed sample sizes or sequential methods for trusty results.
Comparing fixed-horizon and sequential A/B testing methods through real-world case studies. Discover which approach minimizes false positives and acce...
Peeking, p-hacking, and tiny effects: A/B testing is full of traps. Learn from real case studies how to get trustworthy results and avoid common mista...
If you check your A/B test every day and stop when it hits 95% significance, you're probably fooling yourself. Peeking can inflate false positives to ...
Peeking at A/B test results inflates false positives. Learn to pre-commit sample sizes, use sequential testing, and trust practical significance over ...