Expectation, variance, Bayes' rule and entropy — computed from their definitions, so that the notation in later sections reads as arithmetic rather than decoration.
Learning Objectives
→Read E[X] as a weighted sum and compute it without a loop
→Compute variance from its definition and say what squaring buys you
→Apply Bayes' rule, and explain why a positive test on a rare condition is usually a false alarm
→Extract marginal and conditional distributions from a joint table
→Compute entropy in bits, and handle log(0) without producing nan