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Question is quite straight... I'm not very good in this subject but need to understand at a good level.

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what do you mean by probability and to what level do you need it? – picakhu Apr 9 '11 at 3:06
I meant a statistics subject and I want a level that make easier to do exams. The books I have always gaps on explanations and that's make me crazy... – Eduardo Xavier Apr 9 '11 at 3:23
As noted, there are different sorts of "probability". (1) a branch of finite combinatorics (2) assuming knowledge of Riemann integral (maybe even Riemann-Stieltjes integral) (3) presupposing measure theory. Answerers should explain which of these they are talking about. – GEdgar Apr 9 '11 at 14:10
@GEdgar: yes, but even more the questioner should make more precise what he is looking for. It is very inefficient and a waste of people's time to ask for a spray of all possible answers. In fact I think this is as yet not a real question and I am voting to close... – Pete L. Clark Apr 11 '11 at 6:02
@EduardoXavier People can't help you if you're being vague. "a level that makes it easier to do exams" does not tell us anything at all. Other people who ask this same question post a link to the types of probability questions they want to be able to answer. What level of exams are you talking about? A first or second year undergraduate university course? A PhD qualifying exam? An actuarial exam? (And no offense, but deliberate mis-spellings of words is looked down upon on StackExchange forums.) – rocinante Dec 28 '13 at 20:14
up vote 31 down vote accepted

For probability theory as probability theory (rather than normed measure theory ala Kolmogorov) I'm quite partial to Jaynes's Probability Theory: The Logic of Science. It's fantastic at building intuition behind the rules and operations. That said, this has the downside of creating fanatics who think they know all there is to know about probability theory.

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What are readers of this book missing in their understanding of probability theory? – Hatshepsut Jun 24 at 0:17
@Hatshepsut: On the probability side proper, rigorous handling of infinities that don't derive from limiting trends of finite cases, (e.g. measure theory, Borel subalgebras, and all that goodness). It also doesn't cover in any depth several applications that are generally treated as standard, such as Markov chains, random walks, characteristic functions, etc. It certainly doesn't cover enough to say, prepare for a course on stochastic differential equations. – wnoise Jun 24 at 20:47

A First Course in Probability by Sheldon Ross is good.

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I second this, and would like to mention "Probability Theory: A Concise Course" by Y.A. Rozanov – grayQuant May 4 '15 at 1:02

If anybody asks for a recommendation for an introductory probability book, then my suggestion would be the book by Henk Tijms, Understanding Probability, second edition, Cambridge University Press, 2007. This book first explains the basic ideas and concepts of probability through the use of motivating real-world examples before presenting the theory in a very clear way. I found a nice feature of the book the fact that simulation is deliberately used to develop probabilistic intuition. The book also discusses more advanced topics you will not easily find in other introductory probability books. The more advanced topics include Kelly betting, random walks, and Brownian motion, Benford's law, and absorbing Markov chains for success runs. Another asset of the book is a great introduction to Bayesian inference.

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I wouldn't know which book is the best, because I've only used two when I was taking a course in probability, but if you'd prefer videos , I'd suggest:

MIT 6.041SC Probabilistic Systems Analysis and Applied Probability course , which is available in MIT OpenCoursWare for free :

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Here is a list of great books to own to learn probability & statistics. Some on the list like programming in R are great add-on stuff to know.

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While not a book, Sal Khan's site: offers dozens of short videos that provide introductions to probability and statistics. Many of the videos even have problem sets associated with them. Khan provides accessible and often intuitive explanations.

He also has extensive video lessons on algebra, linear algebra, calculus, and geometry as well as physics.

All for free.

Find a discussion on this forum which explores pro's and con's about Khan at:

What does Khan Academy have to offer? Depth? Rigor?

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An Introduction to Probability and Random Processes by Kenneth Baclawski and Gian-Carlo Rota is very good, though it does require the reader to have or develop mathematical maturity.

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I happened to take an introductory course on probability and statistics on two different universities. In one they used a horrible book, and in the other they used a truly amazing one. It's rare that a book really stands out as fantastic, but it did.

Probability and Statistics for Engineers and Scientists by Walpose, Myers, Myers and Ye.

The version number doesn't matter, just find an old version second hand.

It is really thorough, takes one definition at a time, and builds on top of that. The structuring and writing is top class, and the examples are well chosen.

Don't worry if you are not an engineer. When using examples they have taken them from the domain of engineering, eg "A factory produces so and so many items per hour, and only so and so many can be broken, ...", instead of using examples from fx social science or economics. But they don't involve engineering science such as statics, aerodynamics, electronics, thermodynamics or any such things. This means that everyone can understand the book, it does not even help to have an engineering background. Perhaps the examples are more appealing/interesting to engineers, but that's all.

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