•1 min read•from Towards Data Science
Why Most A/B Tests Are Lying to You
Our take
A/B testing is a powerful tool for decision-making, yet many tests yield misleading results due to common statistical pitfalls. In "Why Most A/B Tests Are Lying to You," we explore the four critical statistical sins that can invalidate your findings. This post not only highlights these traps but also provides a practical pre-test checklist to ensure reliability. Additionally, we compare Bayesian and frequentist decision frameworks, equipping you with the insights you need to make informed choices starting Monday.
The 4 statistical sins that invalidate most A/B tests, plus a pre-test checklist and Bayesian vs frequentist decision framework you can use Monday.
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