Principles of Data Science
A/B testing is a method used to compare two versions of a web page, app feature, or marketing material to determine which one performs better. This approach involves splitting traffic between the two variants and analyzing user behavior to identify which version yields higher conversion rates or meets predefined goals more effectively. A/B testing is integral to the data science process as it helps refine decision-making through empirical evidence, while also playing a crucial role in optimizing business strategies in various sectors including finance.
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