Statistical Power - KravitzLab/KreedLabWiki GitHub Wiki
Statistical Power
Statistical power is the probability of detecting a true effect in your sample when it actually exists in the population (i.e., identifying a true positive).
A study with low power may fail to find significance even when a real effect is present, leading you to incorrectly conclude that no effect exists.
Understanding statistical power helps you design experiments that are both reliable and reproducible.
Why It Matters
Statistical power can help you answer key design questions:
- What is the chance my results will replicate if someone else repeats my experiment?
- How many subjects or samples should I include in my study?
Helpful Tools
You can easily estimate power using web-based tools and Python packages:
- Russ Lenth’s Power and Sample Size Applets – simple, interactive calculators
- Statistics Kingdom Power Calculators – accessible web tools for common tests
- Pingouin Stats Package – Python library with built-in power calculators for tests like t-tests and ANOVAs
Learn More
Check out Lex’s Lecture on Power Analyses!