Master new skills with our 21-day learning paths, broken into easy 5-minute daily lessons.
Start your journey for free.
Master new skills with our 21-day learning paths, broken into easy 5-minute daily lessons.
Start your journey for free.
Run valid experiments. Master the statistics behind A/B testing: Sample sizes, Statistical Significance, Frequentist vs Bayesian methods.
Most A/B tests are invalid due to bad math. This course teaches the statistical rigour needed for experimentation. You will learn to calculate Sample Sizes to avoid underpowered tests. Understand P-values, Confidence Intervals, and the difference between Frequentist and Bayesian approaches. We cover common pitfalls like 'peeking' at results too early and Simpson's Paradox. Ensure your data-driven decisions are actually driven by valid data.
Estimated completion time: 21 lessons • Self-paced learning • Lifetime access
Conceptual understanding is key; calculators do the math.
We use generic calculators and industry platforms.
Yes, helps implement feature flags correctly.
Most tests fail; learning *why* is the value.