An Introduction to Probability and Random Processes
by Gian-Carlo Rota, Kenneth Baclawski
Number of pages: 467
The purpose of this course is to learn to think probabilistically. We begin by giving a bird's-eye view of probability by examining some of the great unsolved problems of probability theory. It's only by seeing what the unsolved problems are that one gets a feeling for a field.
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by Paul E Pfeiffer - Connexions
This textbook covers most aspects of advanced and applied probability. The book utilizes a number of user defined m-programs, in combination with built in MATLAB functions, for solving a variety of probabilistic problems.
by Douglas Kennedy - Trinity College
This material was made available for the course Probability of the Mathematical Tripos. Contents: Basic Concepts; Axiomatic Probability; Discrete Random Variables; Continuous Random Variables; Inequalities, Limit Theorems and Geometric Probability.
by Edward Nelson - Princeton University Press
In this book Nelson develops a new approach to probability theory that is just as powerful as but much simpler than conventional Kolmogorov-style probability theory used throughout mathematics for most of the 20th century.
by Cosma Rohilla Shalizi - Carnegie Mellon University
Text for a second course in stochastic processes. It is assumed that you have had a first course on stochastic processes, using elementary probability theory. You will study stochastic processes within the framework of measure-theoretic probability.