Hypothesis Testing

This course provides students with a comprehensive understanding of the theory and application of hypothesis testing in statistics. It introduces the fundamental types of hypotheses and explores advanced methods for evaluating statistical evidence. Students will learn to apply the uniformly most powerful test, construct reliable tests, and utilize key techniques such as the Neyman-Pearson theorem, likelihood ratio test, and sequential probability ratio test. The course also covers the Bayesian approach, ensuring that students acquire both classical and modern perspectives in statistical inference.