Growth & Experimentation

A/B Testing & Experimentation

Run A/B tests you can actually trust

12 lessons4 modules9h 40m durationbeginner level

Instructor: StretchLearn Faculty

About this course

Most A/B tests fail not because the idea was wrong but because the test was run wrong — too small, stopped too early, or read with the wrong math. This course gives you the statistics, process, and tooling that real growth and product teams use, with named platforms, sample-size numbers, and worked examples you can copy. You will leave able to design a valid experiment, calculate how long it must run, and turn results into decisions and a documented program.

Curriculum

Module 1: What Experimentation Is and Why Most Tests Lie3 lessons

The Logic of a Controlled ExperimentPreview45m
The Seven Ways A/B Tests Mislead🔒45m
Where Experimentation Pays Off and Where It Does Not🔒45m

Module 2: The Statistics You Actually Need3 lessons

Hypotheses, Significance, and the p-value🔒50m
Power, Effect Size, and Confidence Intervals🔒50m
Calculating Sample Size and Runtime🔒55m

Module 3: Designing and Running a Clean Test3 lessons

From Insight to a Testable Hypothesis🔒50m
Prioritising the Backlog with ICE and PIE🔒45m
Choosing Tools and Running It Without Contamination🔒50m

Module 4: Reading Results and Building a Program3 lessons

Interpreting the Result Honestly🔒50m
Acting on Wins, Losses, and Flat Tests🔒45m
Building a Culture of Experimentation🔒50m