Use data to make better choices through A/B testing, metrics, and statistical thinking
Chapter 1 · Start here
Metrics That Matter: Vanity Vs Actionable
Learn to distinguish between metrics that look good and metrics that actually drive decisions
Chapter 2 · Start here
A/B Testing: Statistical Significance
Understand when test results are real patterns versus random noise
Chapter 3 · Start here
Correlation Vs Causation: Common Mistakes
Learn why ice cream sales and drowning deaths correlate, but ice cream doesn't cause drowning
Chapter 4 · Start here
Sample Bias: Why Polls Get It Wrong
Understand how sampling errors led to wrong election predictions and business decisions
Chapter 5 · Start here
Statistical Significance: When To Trust Results
Learn the basics of p-values and confidence intervals to make better data-driven decisions
Chapter 6 · Start here
Data Visualization: Seeing Patterns
Discover how the right chart reveals insights instantly while the wrong one obscures truth