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A/B testing statistics, design, increasing sensitivity, multiple experiments comparison, traffic splitting and full A/B testing pipeline in Python

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A/B Testing Advanced Course

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What you'll learn

  • To test hypotheses with complex metrics for which standard tests do not work
  • To develop optimal designs for online and offline experiments
  • To apply modern methods for increasing the sensitivity of A/B tests
  • To conduct multiple experiments in parallel

The Course Syllabus:

  1. Basics of Statistics
  2. Hypothesis testing
  3. Experimental design
  4. Design testing
  5. Confidence intervals
  6. Improving test sensitivity
  7. Metric selection
  8. Cuped
  9. Stratification
  10. Multiple testing
  11. Traffic splitting
  12. Analysis of ratio metrics
  13. Complete A/B testing pipeline

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A/B testing statistics, design, increasing sensitivity, multiple experiments comparison, traffic splitting and full A/B testing pipeline in Python

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