2. A/B Testing Best Practices
Avoid the most common mistakes when setting up an A/B test
A/B tests (aka Split tests) are the most used decision making tool for all product managers. You don’t need advanced knowledge of statistics in order to correctly set up a test (your analytics team does), but you do need to understand some important best practices.
Running A/B tests for an indefinite amount of time, not including a counter-metric in the test, and accidentally P-hacking your own results are examples of common mistakes that product managers make when dealing with A/B tests.
This chapter of the course gets you to avoid these most common mistakes so you can trust your test results.
1. Split tests
3. Best practices
4. Statistical significance
5. Don't run tests "until significance"
Takeaways and Key Lessons- Experiment Design
Exercises - Experiment Design
Exercise Solutions - Experiment design
That's what we recommend. We feel like you'll get the most value that way and you'll learn them easier because there are occasional references to other chapters. However, each chapter has tons of standalone value as well and you will certainly benefit from taking it on its own.
The first chapter of this course is included for free with any signup so you can try the course before choosing to purchase. You can enroll in just that chapter here.