Rao (U. of California, Riverside) continues to build understanding of conditional probability in this comprehensive textbook, which has been completely updated for this edition. He starts with a general overview of the concept of conditioning, including conditioning with densities, the Kolmogorov formulation and its properties including conditional probabilities in the general case and an abstraction, computational problems associated with conditioning, a very interesting axiomatic approach to conditional probability, reviews of the products and regularity of conditional measures, sufficiency, conditions for general structures, and applications to Martingales, Markov and modern analysis processes.