A/B testing compares different versions of a product or service from "summary" of Data Science For Dummies by Lillian Pierson
A/B testing is a valuable tool in the world of data science. It involves comparing different versions of a product or service to determine which one performs better. By conducting A/B tests, organizations can gather data on how small changes impact user behavior and preferences. The process of A/B testing typically involves creating two versions of a product or service - version A and version B. These versions are then presented to users in a randomized fashion, with half of the users seeing version A and the other half seeing version B. By monitoring user interactions with each version, organizations can determine which one yields better results. A key aspect of A/B testing is the need for a control group. This...
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