Hypothesis Testing: Wilks' Theorem and P-Value

This lecture covers hypothesis testing, focusing on Wilks' theorem and the infamous p-value. It explains the likelihood ratio test, Wald's test, and the score test, providing insights into interpreting test statistics and determining evidence against null hypotheses. The lecture also delves into the concept of p-values, their significance, and the interpretation of test results. Additionally, it discusses interval estimation, confidence intervals, pivotal quantities, and challenges in finding exact pivots for various problems, including higher-dimensional parameters.