Hypothesis Testing Lecture
Nowadays, Artificial Intelligence drives scientific and economic growth worldwide. This is largely due to advances in Machine Learning (ML). Its applications span and revolutionize almost every human activity:
-Autonomous Systems (cars, drones, vessels),
-Media Content and Art Creation (including fake data creation/detection), Social Media Analytics,
-Medical Imaging and Diagnosis,
-Financial Engineering (forecasting and analytics), Big Data Analytics,
-Broadcasting, Internet and Communications,
-Robotics/Control
-Intelligent Human-Machine Interaction, Anthropocentric (human-centered) Computing,
-Smart Cities/Buildings and Assisted living.
-Scientific Modeling and Analytics.

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).