/ab-testing-notes

Notes for the A/B Testing course by Google

Primary LanguageJupyter Notebook

A/B Testing Notes

Interview Questions

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Spreadsheets of Tracking & Calculating Statistical Significance

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Statistical Significance Calculator

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Google's Course

Notes for the A/B Testing course by Google

  1. Overview
  2. Metric Choice
  3. Statistics
  4. Design
  5. Analyzing Results
  6. Ethics
  7. Final Project

Overview

  • When can you use A/B testing?

Metric Choice

  • Customer Funnel
  • Click-Through-Rate (CTR) vs Click-Through-Probability
  • Invariant Checking
  • Evaluation
  • Gathering Additional Data
  • Choosing a Technique
  • Defining a Metric
  • Filtering and Segmenting
  • Summary Metrics
  • Sensitivity vs Robustness

Statistics

  • Binomial Distribution
  • Confidence Interval
  • Margin of Error
  • Hypothesis Testing/Inference
  • Pooled Standard Error
  • Statistical Power
  • Sensitivity
  • Absolute vs Relative Changes
  • Variability
  • Non-parametric Methods

Design

  • Sample Size Calculator
  • Example

Analyzing Results

  • Sanity Checks
  • Single Metric Evaluation
  • Simpson’s paradox
  • Multiple Metrics
  • Disappearing Launch Effect

Ethics