Allon Korem | CEO, Bell StatisticsinBellOne tailed vs. two tailed testsChoosing between one and two-tailed hypothesis affects every stage of A/B testing. Learn why, and explore the pros & cons of each approach.Nov 6Nov 6
Allon Korem | CEO, Bell StatisticsinBellIt’s normal not to be normal(ly distributed) — what to do when data is not normally distributedWhy deviations from normality are often not a significant concern in A/B testing, and what are the alternative methods to t-testOct 21Oct 21
Allon Korem | CEO, Bell StatisticsinBellWhy the uplift in A/B tests often differs from real-world resultsExplore why the uplift seen in A/B tests often differs from real-world outcomes, and get insights on how to manage expectations…Sep 8Sep 8
Allon Korem | CEO, Bell StatisticsinBellSize matters: How to plan test duration when using CUPEDLearn how to use CUPED, a powerful technique that enhances the sensitivity of your tests and helps in resource optimization.Aug 18Aug 18
Allon Korem | CEO, Bell StatisticsinBellTL’DR: Bayesian A/B testing falls shortThere’s a disconnect between the industry’s enthusiasm for Bayesian testing and its actual contribution, validity, and effectiveness.Jun 261Jun 261
Allon Korem | CEO, Bell StatisticsinBellFour Ways to Improve Statistical Power in A\B Testing (without increasing test duration, duh)Learn how Allocation, Effect Size, CUPED & Binarization can help you improve statistical power without prolonging test durations.May 22May 22
