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Rating: 
Summary: delightful introduction to probability
Review: Professor Isaac has written a book for those interested in learning about probability. It is at a high school algebra level although knowledge of calculus could be helpful at times. He starts with the now famous Monte Hall problem and provides the most lucid explanation I have seen to date. This is a great way to introduce important probability notions such as sample space and probability models for the sample outcomes. Deals mainly with discrete probability which is easiest to understand and yet rich with applications in gambling and other areas. Important theory is presented but without the detailed mathematical proofs. Covers the gambler's ruin, geometric probability, Monte Carlo methods and some statistical decision theory. He also presents both the frequentist (throughout the text)and the Bayesian paradigms (Chapter 4) for statistical inference. Examples of the application of probability to statistical inference is nicely treated in Chapter 15. The deeper material on Markov chains and Brownian motion are relegated to the last two chapters (16 and 17). The exposition is excellent throughout and many good references are provided for readers who want to learn more or delve deeper into the theory.
Rating:
Summary: Excellent introduction
Review: This introduction to probability and statistics teaches you about important concepts, theorems and applications without going into proving most of them. It's easily accessible to amateur mathematicians with a bit of persistance, and it illuminates many of its concepts using famous problems. I'm going to take a statistics course next year, and I found this to be a delightful introduction to the topic.
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