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| Statistics, 4th Edition
Hardcover
Edition: 4th
Author: David Freedman, Robert Pisani, Roger Purves
Publisher: W. W. Norton
Release Date: 2007-03-19
ISBN-10: 0393929728
ISBN-13: 9780393929720
List Price: $106.95
Average Customer Rating:
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Summaries and Customer Reviews are supplied by Amazon.com
In its first edition, Statistics set a new standard for introductory texts, written in accessible language that teaches students how to think about statistical issues through real-world examples, such as political polls and Galton's regression paradox, and in terms of models that underlie statistical inference. Retaining these core strengths, the Fourth Edition adds a diverse body of new examples, exercises, and data sets, and has been thoroughly updated to reflect the most recent developments in the field.
Excellent Approach for Beginners
| Customer Rating: | | An excellent intuitive approach to presenting statistics, a subject that can be baffling to the beginner. |
Endless Chatter
| Customer Rating:  | No clear examples.
Unfocused style.
Celebration of ignorance.
Overpriced at 0.01+shipping.
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Excellent Introductory Text
| Customer Rating: | After having progressed through the first 11 chapters of this text, I feel that this text has easily become one of my favorites.
The text uses various real-life case studies (some examples that come to mind are height and weight, IQ, and drug studies) that it will revisit throughout the text. They are, more often than not, interesting and help underscore the practicality of statistics. You cannot go more than several paragraphs without getting involved in a case study.
Although this text is not math-intensive, it does foster something much more useful than an understanding of mathematical equations; it teaches you to think critically about the information that is presented and the questions that are asked of you. To be able to think critically and understand statistics is of the utmost importance, as everyday statistics is, in some way or another, used to justify something. Statistics can be a dangerous tool, and if you don't have a good knowledge of statistics, you may become of a victim of it; the book clearly highlights this fact with examples such as the NFIP vaccination studies, the use of ecological correlations commonly used in political science and sociology, and various observational studies.
If you want math and nothing but math, do not buy this book.
If you want an engaging text with practical examples that will help you to think critically about not only statistics, but also about information in general, I would strongly suggest purchasing this text.
I would also suggest purchasing this item if you want a text that will help you understand the "why" of statistics, not just the "how". |
A famous edition
| Customer Rating: | | A famous edition of an old standard for stats and I gave this to someone as a gift but knew of it and was told by him that it is still one of the best books on the subject matter. |
great for a first course to non-statistics majors
| Customer Rating: | Many introductory statistics texts suffer from one of two ailments. Either they incorporate too much mathematics for non-statisticians or they provide oversimplified and sometimes incorrect explanations. This text is excellent and is favored by many statisticians who teach the introductory service course for non-statistics majors. The book provides excellent and insightful explanations. It is written by well-known Berkeley statisticians with great theoretical and applied experience, so it is not oversimplified or inaccurate. On the other hand Friedman and his co-authors took pains to minimize the necessary mathematics. It covers all the topics one would want to include in a first course. Real examples are used throughout to illustrate the value of the methods. These include clinical trials and observational studies, telephone surveys and opinion polls and some models in genetics.
Discussion of the data snooping issue is important, particularly as we move into an age where data mining is now feasible with current computing power.
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