The Logic Of Chance
by John Venn
Publisher: Macmillan And Company 1888
Number of pages: 550
No mathematical background is necessary to appreciate this classic of probability theory. Written by the logician who popularized the famous Venn Diagrams, it remains unsurpassed in its clarity, readability, and charm. The treatment commences with an overview of physical foundations, examines logical superstructure, and explores various applications.
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by H.R. Pitt - Tata institute of Fundamental Research
Measure Theory (Sets and operations on sets, Classical Lebesgue and Stieltjes measures, Lebesgue integral); Probability (Function of a random variable, Conditional probabilities, Central Limit Problem, Random Sequences and Convergence Properties).
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 Davar Khoshnevisan, Firas Rassoul-Agha - University of Utah
This is a first course in undergraduate probability. It covers standard material such as combinatorial problems, random variables, distributions, independence, conditional probability, expected value and moments, law of large numbers, etc.