Conditional Probability: Understanding Independence

This lecture covers the concept of conditional probability, defining it as the probability of an event given another event has occurred. Examples include the probability of rolling an even number on a die. It also explains independence between events, where the occurrence of one event does not affect the other. The lecture further explores pairwise and mutual independence, illustrating scenarios with dice rolls. It delves into the use of side information in decision-making, such as betting on dice outcomes based on observed properties. The session concludes with practical examples and calculations to solidify the understanding of these fundamental probability concepts.