Introduction to Probability

by Dimitri P. Bertsekas

An intuitive, yet precise introduction to probability theory, stochastic processes, and probabilistic models used in science, engineering, economics, and related fields. The 2nd edition is a substantial revision of the 1st edition, involving a reorganization of old material and the addition of new ...

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Genres: Mathematics, Textbooks, Computer Science, Science, Nonfiction, Technology, Academic

ebook

First published June 24, 2002

Reviews

[Franta · Rating 5 out of 5]

Well done textbook introducing all the main topics in probability, as well as Markov Chains, Bayesian Statistical Inference, and Classical Statistical Inference.
I would also recommend the free MIT course at edX, Introduction to Probability - The Science of Uncertainty, taught by the author of this book, John Tsitsiklis.

[Laura Uzcategui · Rating 5 out of 5]

Back in University I remember how hard was for me to get Probability, still was a fascinating topic but by that time I couldn't grasp the concepts properly, earlier this year I got back to it by taking a class from MIT open courseware and it was fantastic, I used this textbook as compliment, did the exercises and went through the majority of the explanations and tbh it was really good experience going from almost nothing to having a grasp of probability theory and how important is in real applications and life in general. Totally recommend this book.

[Nidhal Ben Tahar · Rating 4 out of 5]

I took MITx-6.431x on edX, that's what brought this book to my hands.
The chapters are full of examples, and the problems are challenging and fun. There are hundreds of them by the way. Of course, challenging can also be "unfun" and I felt sometimes out of my flow zone, but I believe it's worth the efforts put into it.

[Роман Вашурин · Rating 4 out of 5]

The statistics part seems a bit rushed, but the probability chapters are great, very clear, notation is clear and consistent throughout the book, problems are quite challenging. At times it seems that authors did not assume any prior mathematical knowledge of the reader, which makes certain parts look odd, like looking at Markov processes without using any matrix algebra. Otherwise this is a great introductory probability text for self-learners.

[Bubu · Rating 5 out of 5]

Excluding Bayesian part :(

[Xin Yang · Rating 5 out of 5]

This book is absolutly 5 five star for me. I took the similar class in university more than 10 years ago and had never understood what probability is (maybe some little classic probablity). These days my work is all about randomness and push me to study the ideas in probability again. It's very tough for a guy who had gradutaed for more than 10 years, but the book offers a fast pace course (MIT 6.041) which helps me grasp the key ideas and read the whole book quickly.

[Ahmad A. · Rating 4 out of 5]

Textbook used as part of the MITx course "Probability Theory: The Science of Uncertainty", written by the same course instructors. Very good resource, I think people interested in the subject can even pick up the book without the guidance of the course and still learn a lot from it.

MITx course: https://www.edx.org/course/probabilit...

[Daniel F. · Rating 5 out of 5]

A comprehensive and well-written introduction to probability theory and statistics. I particularly appreciated the careful attention to notation and the formal yet straightforward. Some of the exercises can be hard so if you don't have experience, some patience is needed when going through them.

[Mahammad Valiyev · Rating 5 out of 5]

A solid book on applied probability, random processes, and statistical inference with intuitive explanations and challenging problem sets. Would highly advise going over MIT OCW course 6.041SC in parallel while reading the book.

[Jacky Han · Rating 4 out of 5]

Great clarity and not-too-dry illustration. I wished I had this book back in college...

[Ron Horner · Rating 5 out of 5]

This is an excelent introduction to calculus based probability. It is easily accessible to people coming from any dicipline.

I read it as part of my graduate studies at GMU (ECE 528).