This lecture covers the chi-squared test for hypothesis testing against a theoretical probability distribution. It explains how to determine if observed data significantly deviates from the expected distribution, using the chi-squared statistic. The lecture also demonstrates the application of the chi-squared test through examples, such as testing the fairness of dice. Key concepts include hypothesis formulation, significance level determination, computation of the test statistic, critical region identification, and decision-making based on the test results.