Customer Reviews

Introduction to Probability

5 star:		(4)
4 star:		(1)
3 star:		(0)
2 star:		(0)
1 star:		(0)

 

 

This is a wonderful book on probability theory.
I first used it at Dartmouth in an intro course 12 years ago, and I still find it illuminating.

The level is at once highly rigorous and extremely readable & engaging. I believe anyone can read this book (a smattering of first-year calculus would help to understand the sections on continuous probability distributions).

The paradoxes in Chp 4 are memorable, as is the medical question on false positives / false negatives, which most med students failed.

With a chapter on random walks, this is also the perfect introduction for anyone in physics / finance seeking to study stochastic calculus.

Truly, there's nothing that is
(a) more clearly written
(b) more enjoyable to read (if you like math)

This book is freely available under the GNU General Public License, in PDF format. The GPL allows free usage to anyone, and free modification and redistribution with the restriction that your changes have to remain free under the same license. This is the same license Linux and much open source software is released under.

Try a web search for the authors/title. For a course, you might want to purchase the physical copy anyway.

I am starting on the book now, so ignore my rating of the book itself - I had to include a rating to post.

A good variety of problems, easy, medium, and hard. I was able to read through the chapters and understand the mathematics. The computer programs truly complement the sections.

I used this book when I taught Probability last Summer and I thought the book was excellent. The book is full of illuminating examples and the exercises are really good to enhance the material.

My favorite chapter is Chapter 9, were they teach the Central Limit Theorem.

Another great chapter is 11 where the book deals with Markov Chains. Markov chains are great for applications in the real world and the chapter is written very clearly.

The book covers Discrete Probability, Continuous Probability, Permutations, Combinations, Conditional Probability, Expectation, Variance, Poisson Distribution, Normal Distribution, Law of Large Numbers, Central Limit Theorem, Markov Chains and Random Walks. It covers everything one needs for an introductory probability course.

covers fundamentals well, easy to read, good variety of problems, historic sections are interesting