Introduction to Probability
by Davar Khoshnevisan, Firas Rassoul-Agha
Publisher: University of Utah 2012
Number of pages: 269
This is a first course in undergraduate probability. It requires a solid knowledge of Calculus (I, II, III), and covers standard material such as combinatorial problems, random variables, distributions, independence, conditional probability, expected value and moments, law of large numbers, and the central limit theorem.
Home page url
Download or read it online for free here:
by Oliver Knill - Overseas Press
This text covers material of a basic probability course, discrete stochastic processes including Martingale theory, continuous time stochastic processes like Brownian motion and stochastic differential equations, estimation theory, and more.
by Robert B. Ash - Dover Publications
This text surveys random variables, conditional probability and expectation, characteristic functions, infinite sequences of random variables, Markov chains, and an introduction to statistics. Geared toward advanced undergraduates and graduates.
by John Venn - Macmillan And Company
No mathematical background is necessary for this classic of probability theory. It remains unsurpassed in its clarity, readability, and charm. It commences with physical foundations, examines logical superstructure, and explores various applications.
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.