An intuitive, yet precise introduction to probability theory, stochastic processes, and probabilistic models used in science, engineering, economics, and related fields.

The book covers the fundamentals of probability theory (probabilistic models

The book covers the fundamentals of probability theory (probabilistic models, discrete and continuous random variables, multiple random variables, and limit theorems), which are typically part of a first course on the subject. It also contains, a number of more advanced topics, including transforms, sums of random variables, least squares estimation, the bivariate normal distribution, and a fairly detailed introduction to Bernoulli, Poisson, and Markov processes.

The book strikes a balance between simplicity in exposition and sophistication in analytical reasoning. Some of the more mathematically rigorous analysis is explained intuitively in the text, and is developed in detail (at the level of advanced calculus) in the numerous solved theoretical problems.

This text is being currently used in introductory probability classes at several universities, including M.I.T., Berkeley, and Stanford. ...Continua

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