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Rating: Summary: Excellent text Review: I taught an introductory statistics course with this book two years ago. I have to say that *I* learned a great deal preparing for class as I read it--there is a lot of insight and intuition here that you won't generally find anywhere else. Teaching out of it is tough, though, because you don't have the math to hide behind. For those of us used to math, formulas can be a comforting thing. For most students, they're usually just intimidating and the object of many blank stares. IMO, for students who will take only one class in statistics, learning out of this book would be very helpful in a way many other books would not be. For students who will take more than one, gaining a strong conceptual foundation will be helpful as well. My guess is that the students complaining about this book don't know how good they've got it. You could be stuck with a book that focuses on how to do statistics with Excel or the like, in which case you'll basically learn nothing of subsequent value. :)
Rating: Summary: great introductory texts Review: 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.
Rating: Summary: Statistics by David Freedman Review: Useful book. Lots of helpful examples. Don't really need any extra stats resources (like a workbook) if you buy this.
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