STATISTICS

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. :)


A good start..   July 20, 2001
Drew Balazs (Indianola, WA United States)
122 out of 127 found this review helpful

If you are looking for a good (non-technical i.e. not involving higher math) introduction to statistics, this is the book for you. As a TA at Cal (Berkeley..Go Bears!), I worked for Roger Purves (one of the authors of the book) and I taught out of this book. Needless to say, I got to know the book rather well. I highly recommend it.

However, if you are looking for a slightly more advanced introduction to statistics/probability, I would suggest something along the lines of Probability by Jim Pitman or Mathematical Statistics and Data Analysis by John Rice. If you are really serious about probability theory, you might want to try Statistical Inference - by G. Casella and R.L. Berger.


Buy this book and you won't regret it!   November 22, 2000
macktheknife (Northern, CA)
36 out of 38 found this review helpful

I had used this book for my Introduction to Statistics class, and I think it was the best $60 I had ever spent. The authors explain all the major statistical concepts clearly and succinctly, drawing on a variety of samples and adding a touch of humor. The math in this book is more than doable; anyone with a basic grasp of algebra and a willingness tackle numbers is the only prerequisite to understanding this book. However, the authors also try to convey to the reader that there is more to statistics than just numbers. How an experiment is constructed, how polls are taken, what biases exist, and how assumptions are made are all integral parts of statistics. This book is applicable to almost every subject--political science, sociology, sciences, engineering, etc. There are enough exercises in the chapters to assist the reader in reviewing the concepts. I can't stress this enough: Buy this book and you won't regret it!


very good introduction   October 16, 2000
MonkGroupie (United States)
7 out of 9 found this review helpful

This is an excellent introduction to the subject, especially if your math background is close to nill. If you feel confortable with elementary mathematics, (e.g. a little calculus and a little linear algebra) then the book is still very useful, especially in explaining the intuitive aspects of the field. However, even the handy companion workbook "Mathematical Methods in Statistics", which does use a little bit of mathematics, is quite elementary. Unfortunately, there are no introductory Statistics books aimed at those who know a little bit of mathematics, so this book is pretty much all there is (with the exception of the new Nolan & Speed book). Overall, I think this is a really wonderful book, and if you do have a little bit of math background, it reads like a novel. It is extremely comprehensive for an introduction, and experienced statistics students will often use this book as a reference. There could be a little more attention paid to the mathematically confortable readers (at least in the workbook: the treatment of regression for example could at least mention the linear alebra.) As well, it would be very useful to touch upon some statistical software (e.g. Splus)


Fantastic!   May 3, 2000
14 out of 15 found this review helpful

This book is a rare gem. You can find piles of books with Statistics symbols/equations and hard-core problems, but how many of them really teach you the meaning of what you're doing?

Statistics is a kind of data-compression - you start off with with a bag of data and you extract certain "features" such as averages, standard deviations etc... ...this allows you to say general things about the entire dataset (avg/SD, etc.) or claim associations between multiple datasets with varying degrees of confidence (correlations) or even predict the value of one variable if you know the other (regressions).

The dangerous thing is, if you are not careful about how you "compress" this data or about what you do or don't do with the dataset (like dealing with outliers), your conclusions may be ENTIRELY INVALID! By using specific examples, this book teaches you to look at what are you doing before you do the analysis and then how to look at your results after you do your compression (running statistical studies).

I was reluctant to buy this book at the bookstore at first, but after having read the entire text, I believe this investment was money well spent. If you don't believe me, check it out in a bookstore before you buy the book.

Good luck!