This lecture overviews Hypothesis Testing that has many applications in statistics and pattern recognition. It covers the following topics in detail: Elementary Principles, NSHT & BHT, Tests: Tests comparing mean values (T-test, Z-test), Tests detecting normal distribution (Chi-Squared test, Mardia’s test), Tests determining distribution type (Anderson-Darling Test, Kolmogorov-Smirnov Test).
