Linearity of Expectations: Theorem and Inversions in Permutations

This lecture covers the linearity of expectations theorem, stating that the expected value of the sum of random variables is the sum of their individual expected values, along with examples and proofs. It also discusses inversions in permutations, defining them as pairs where the larger element precedes the smaller one, and explores the expected number of inversions in a permutation.