A Treatise on Probability
by John Maynard Keynes
Publisher: Macmillan and co 1921
Number of pages: 561
From the table of contents: Fundamental ideas - The Meaning of Probability, The Measurement of Probabilities; Fundamental theorems; Induction and analogy; Some philosophical applications of probability; The foundations of statistical inference, etc.
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by Robert M. Gray - Springer
A self-contained treatment of the theory of probability, random processes. It is intended to lay theoretical foundations for measure and integration theory, and to develop the long term time average behavior of measurements made on random processes.
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.
by Rick Durrett - Cambridge University Press
An introduction to probability theory covering laws of large numbers, central limit theorems, random walks, martingales, Markov chains, ergodic theorems, and Brownian motion. It concentrates on the results that are the most useful for applications.
by William G. Faris - University of Arizona
From the table of contents: Combinatorics; Probability Axioms; Discrete Random Variables; The Bernoulli Process; Continuous Random Variables; The Poisson Process; The weak law of large numbers; The central limit theorem; Estimation.