Sampling and Estimation
Sampling distributions, the Central Limit Theorem, point estimation, confidence intervals, and margin of error.
Hypothesis Testing Foundations
The logic of hypothesis testing, formulating null and alternative claims, Type I and Type II errors, test power, and decision rules.
Large Sample Tests
One-sample and two-sample Z-tests, decision rules across critical values, p-values, and confidence intervals with Python implementations.