- Paperback: 568 pages
- Publisher: Cambridge University Press; 1st edition (2 Aug 2001)
- Language English
- ISBN-10: 052100618X
- ISBN-13: 978-0521006187
- Product Dimensions: 2.5 x 1.8 x 0.3 cm
- Average Customer Review: 5.0 out of 5 stars See all reviews (2 customer reviews)
- Amazon Bestsellers Rank: 618,390 in Books (See Top 100 in Books)
- See Complete Table of Contents
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More About the Author
Product Description
Review
'David Williams is a very distinguished mathematician with an enthusiasm for the subject which lights up the book. The book should be read, and the contents pondered on, by everyone who teaches 'second courses' on probability or statistics in a mathematics degree; any good student on such courses would surely be excited by the book.' LTSN Newsletter
'In the Preface the author warns that the book has many unusual features: this is why the book is so interesting. The book is a rich and enjoyable source of ideas, motivations and examples, which can be used by teachers of probability and statistics.' EMS
'David Williams, an author well known in the probabilists' community, has written several books which have had an important influence from the moment they were published. In summary, while progressing through the book, the reader evolves from elementary questions of heads and tails toward a global vision of probability and statistics, with the author vowing to reconcile these two domains, which have separated, then divorced. It is a goldmine of information in both domains. Bravo, David, for this new tour de force! Many readers will be looking forward to your next volume, but this should not distract you from l'art d'etre grand-père, especially in the bicentennial year of Victor Hugo.' The Mathematical Intelligencer
'I think this is a must-read book for all who will eventually work and teach in probability or statistics because it affords an enjoyable, accessible, and important perspective about their interrelationships.' Computing in Science & Engineering
'… the book?s unusual approach and entertaining style results in an introduction to statistics which is unusually accessible to an applied mathematics audience … a very readable book, from which I learned a great deal and into which I have been continuously dipping since I finished it. I would recommend it to anyone, from final year undergraduate, to an established researcher in nonlinear science. They might be surprised how interesting statistics can be, and perhaps respond more positively next time they are asked to fit data to a model.' Nonlinear Science News
'In the Preface the author warns that the book has many unusual features: this is why the book is so interesting. The book is a rich and enjoyable source of ideas, motivations and examples, which can be used by teachers of probability and statistics.' EMS
'David Williams, an author well known in the probabilists' community, has written several books which have had an important influence from the moment they were published. In summary, while progressing through the book, the reader evolves from elementary questions of heads and tails toward a global vision of probability and statistics, with the author vowing to reconcile these two domains, which have separated, then divorced. It is a goldmine of information in both domains. Bravo, David, for this new tour de force! Many readers will be looking forward to your next volume, but this should not distract you from l'art d'etre grand-père, especially in the bicentennial year of Victor Hugo.' The Mathematical Intelligencer
'I think this is a must-read book for all who will eventually work and teach in probability or statistics because it affords an enjoyable, accessible, and important perspective about their interrelationships.' Computing in Science & Engineering
'… the book?s unusual approach and entertaining style results in an introduction to statistics which is unusually accessible to an applied mathematics audience … a very readable book, from which I learned a great deal and into which I have been continuously dipping since I finished it. I would recommend it to anyone, from final year undergraduate, to an established researcher in nonlinear science. They might be surprised how interesting statistics can be, and perhaps respond more positively next time they are asked to fit data to a model.' Nonlinear Science News
Product Description
Statistics do not lie, nor is probability paradoxical. You just have to have the right intuition. In this lively look at both subjects, David Williams convinces mathematics students of the intrinsic interest of Statistics and Probability, and Statistics students that the language of mathematics can bring real insight and clarity to their subject. He helps students build the intuition needed, in a presentation enriched with examples drawn from all manner of applications, e.g., genetics, filtering, the Black-Scholes option-pricing formula, quantum probability and computing, and classical and modern statistical models. Statistics chapters present both the Frequentist and Bayesian approaches, emphasising Confidence Intervals rather than Hypothesis Test, and include Gibbs-sampling techniques for the practical implementation of Bayesian methods. A central chapter gives the theory of Linear Regression and ANOVA, and explains how MCMC methods allow greater flexibility in modelling. C or WinBUGS code is provided for computational examples and simulations. Many exercises are included; hints or solutions are often provided.
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Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
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Customer Reviews
Most Helpful Customer Reviews
1 of 1 people found the following review helpful
Format:Paperback
A book that is different, indeed, but this difference is what makes it interesting. It bridges the gap between the teaching of Probability and Statistics, and does so in style. The book is accessible to undergraduate students, especially those who are accustomed to learning by thinking (alas, an endangered species). and not by rote
Format:Paperback
This is one of the few textbooks on probability and statistics where everything is explained thoroughly. It is recommended for those who prefer to understand everything that is going on without necessarily getting bogged down in all the details.
Most Helpful Customer Reviews on Amazon.com (beta)
Amazon.com:
8 reviews
12 of 15 people found the following review helpful
vintage williams
9 Jun 2003
Format:Paperback
This is a delightful introduction to probability and mathematical statistics. There are already quite a few nice probability texts at this level (Jim Pitman's PROBABILITY is a favorite of mine) and many serviceable introductions to mathematical statistics (Rice's MATHEMATICAL STATISTICS AND DATA ANALYSIS and Cassella & Berger's STATISTICAL INFERENCE are good examples), but Williams is very different from these. He manages to teach a lot of beautiful probability along with some practical statistics. The approach is thoroughly modern (including in depth coverage of modern Bayesian methods) and reasonably applied (much more applied than you would expect from his other books). He is opinionated, but never boring.
The only negatives I can think of are (1) too few problems, especially easy problems; (2) quite a few typos--it's a first printing; and (3) some asides, especially on measure theoretic issues, that the target audience may find more confusing than helpful.
I wish this book had been around when I first studied this material.
3 of 3 people found the following review helpful
Beautiful Book
29 May 2009
Format:Paperback
The biggest problem with this book is that it might require a bit background to appreciate. To be fair to the author he makes this very clear on the first page of the preface, that it's intended for two types of people: (1) people with at least a year of probability/statistics and are familiar with the mechanics (2) people with pure math backgrounds. I fit in both categories and found the book very enjoyable. If you're neither, you'll probably find the book confusing. So most likely it won't be a good intro text or reference book or the only probability/statistics book you'll ever open, if you don't have a math background. (If you have to buy Sheldon Ross's book to make sense out of a course, this book was not intended for you...)
That aside the book is really beautifully written. He has a bit of a rambling style, probably because the book came from a class he taught, according to the preface. So there are q&a's, side remarks, and all the examples/exercises are actually interesting and important. Someone complained about lack of proofs - you can find them in any standard text, but the intuition is much more valuable in order to make the material more than just mechanical. If you're like me and know what it feels like to have a bad professor who just copies the textbook line by line on the board without bothering to actually communicate with you, this is the opposite. It's amazing that he's distilled so much insight into this book and made it so accessible.
That aside the book is really beautifully written. He has a bit of a rambling style, probably because the book came from a class he taught, according to the preface. So there are q&a's, side remarks, and all the examples/exercises are actually interesting and important. Someone complained about lack of proofs - you can find them in any standard text, but the intuition is much more valuable in order to make the material more than just mechanical. If you're like me and know what it feels like to have a bad professor who just copies the textbook line by line on the board without bothering to actually communicate with you, this is the opposite. It's amazing that he's distilled so much insight into this book and made it so accessible.
12 of 16 people found the following review helpful
In common justice
5 Sep 2004
Format:Paperback
It seems only fair to remark that the invective directed against the book by some Amazon customers is something profoundly different in kind from what one finds in reviews by authoritative people. See, for example, the detailed reviews by Ed Waymire in American Mathematical Monthly, Vol. 110, 2003, pp. 964-967, and by Marjorie Hahn in Computing in Science and Engineering, Vol. 6, 2004, pp. 85-88. In forty years of teaching probability theory, I have had very many students who would not have found a book such as this particularly challenging, but who would have welcomed what challenges it does pose.
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