“Observed power”, “Post hoc Power”, and “Retrospective power” all refer to the statistical power of a statistical significance test to detect a true effect equal to the observed effect. In a broader sense these terms may also describe any power analysis performed after an experiment has completed. Importantly, it is the first, narrower sense that […] Read more…
The above is a question asked by some practitioners of A/B testing, as well as a number of their clients when examining the outcome of an online controlled experiment. It may be raised regardless if the outcome is statistically significant or not. In both cases the fact the observed effect in an A/B test is […] Read more…
One topic has surfaced in my ten years of developing statistical tools, consulting, and participating in discussions and conversations with CRO & A/B testing practitioners as causing the most confusion and that is statistical power and the related concept of minimum detectable effect (MDE). Some myths were previously dispelled in “Underpowered A/B tests – confusions, […] Read more…
How long does a typical A/B test run for? What percentage of A/B tests result in a ‘winner’? What is the average lift achieved in online controlled experiments? How good are top conversion rate optimization specialists at coming up with impactful interventions for websites and mobile apps? This meta-analysis of 1,001 A/B tests analyzed using […] Read more…
In recent years a lot more CRO & A/B testing practitioners have started paying more attention to the statistical power of their online experiments, at least based on my observations. While this a positive development for which I hope I had contributed somewhat, it comes with the inevitable confusions and misunderstandings surrounding a complex concept […] Read more…
Take your A/B testing program to the next level
Want to take your A/B tests to the next level?
If you enjoyed this article and want to read more great content like it make sure to check out the book “Statistical Methods in Online A/B Testing” by the author, Georgi Georgiev, and take your experimentation program to the next level.