A/B testing, also known as split testing, helps businesses optimize conversion rates by experimenting with different webpage versions. The post compares frequentist and Bayesian methods for analyzing A/B test results. It highlights the limitations of the Chi2 test in frequentist settings and demonstrates Bayesian modeling using

8m read timeFrom towardsdatascience.com
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An Introduction to Bayesian A/B TestingComparing Conversion RatesModel Arbitrary Data-generating ProcessesConclusion

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