Bayes' Theorem: Defective Parts Detection

This lecture covers the application of Bayes' Theorem in detecting defective parts in a production plant. It explains how to calculate the probability of a part being defective given the test results. The lecture also discusses discrete random variables, mass functions, and distribution functions. Examples are provided to illustrate the concepts, such as rolling dice and drawing cards. The instructor, Erwan Koch from EPFL, presents practical scenarios like testing water quality and predicting the number of people with birthdays in a group. The lecture concludes with exercises on binomial and Poisson distributions, emphasizing the importance of probability calculations in real-world applications.