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A/B Testing with ML ft. Michael Berk - ML 181

Adventures in Machine Learning

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A/B Testing Insights: Navigating Variance and Methodologies

This chapter explores the fundamentals of A/B testing, contrasting frequentist and Bayesian approaches, and emphasizes the significance of determining sample sizes for reliable outcomes. Additionally, it addresses the role of variance in data analysis, the application of forecasting methods, and the integration of these principles in optimizing business decisions and ad revenue.

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