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#38 Data Products, Dashboards and Rapid Prototyping

DataFramed

CHAPTER

How Important Is Power in Your Tests?

The observed significance level of a test, the p value, also determines the observed power. Non significant p values always correspond to low observed powers. A higher p value is usually taken as more evidence for the null hypothesis. But lower power takes as less evidence for thenull interesting. How is power being important in your own work? Power is a critical concept in a b testing. If you don't do a power analysis, you can fall victim to a problem called peking where you check every day whether there's a significanc difference between groups and stop the test. This will result in a huge increase in your false positive rate.

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