Well known for the clear, inductive nature of its exposition, this reprint volume is an excellent introduction to mathematical probability theory. It may be used as a graduate-level text in one- or two-semester courses in probability for students who are familiar with basic measure theory, or as a supplement in courses in stochastic processes or mathematical statistics. Designed around the needs of the student, this book achieves readability and clarity by giving the most important results in each area while not dwelling on any one subject. Each new idea or concept is introduced from an intuitive, common-sense point of view. Students are helped to understand why things work, instead of being given a dry theorem-proof regime.
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This reprint volume is an excellent introduction to mathematical probability theory, suitable for graduate-level use in probability courses or as a supplement for courses in stochastic processes or mathematical statistics. The readability and clarity of the style help students understand why things work, instead of handing them a theorem-proof regime.
Leo Breiman is professor and director of the statistical computing facility in the statistics department at the University of California at Berkeley. He is a fellow of the American Statistical Association and the Institute of Mathematical Statistics.
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