This material assumes the user has the background provided by a good undergraduate course in applied probability. It is felt that introductory courses in calculus, linear algebra, and perhaps some differential equations should provide the requisite experience and proficiency with mathematical concepts, notation, and argument. The document is divided into five major sections, each concluding with a set of exercises. The major parts are entitled: (A) Preliminaries; (B) Conditional Independence of Events; (C) Conditional Expectations; (D) Conditional Independence, Given a Random Vector; and (E) Markov Processes and Conditional Independence. The document includes three appendices, a brief list of references, and a presentation of selected answers, hints, and key steps. (MP)