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This lecture delves into the interpretation of entropy, focusing on the concept of entropy expressed in bits and its relation to probability distributions. Starting with the basics of normalization and entropy calculation, the instructor explains how entropy is related to information gain and loss in scenarios like coin flips and dice rolls. The lecture further explores the quantification of randomness, information, and statistical dependence between random variables. It concludes with a discussion on the entropy of different probability distributions and the challenges in estimating probabilities from experimental data.