A Guide to A/B Testing as a Data Scientist

A Guide to A/B Testing as a Data Scientist

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Issue of Interpretability

5 of 14

5 of 14

Issue of Interpretability

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A Guide to A/B Testing as a Data Scientist

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  1. 1 Introduction
  2. 2 Experiment Definition
  3. 3 Create Dataset for A/B Test
  4. 4 Hypothesis Testing
  5. 5 Issue of Interpretability
  6. 6 Bayesian Testing: Constructing Prior
  7. 7 Bayesian Testing: Constructing Posterior
  8. 8 Introducing a Continuous Metric: Prices
  9. 9 Understand Pricing Distributions
  10. 10 Add prices to dataset
  11. 11 Bayesian Math
  12. 12 Coded Math
  13. 13 Construct Priors, Posteriors
  14. 14 Interpret Results for Continuous Metric

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