Hypothesis Testing Foundations
The logic of hypothesis testing, formulating null and alternative claims, Type I and Type II errors, test power, and decision rules.
Probability of observing sample data as extreme as obtained, assuming H0 is true.
View all tagsThe logic of hypothesis testing, formulating null and alternative claims, Type I and Type II errors, test power, and decision rules.
One-sample and two-sample Z-tests, decision rules across critical values, p-values, and confidence intervals with Python implementations.