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| Introduction to the Practice of Statistics w/CD-ROM | 
 enlarge | Buy New: $17.98
Buy New/Used from $17.98
Avg. Customer Rating:   (based on 14 reviews)
Sales Rank: 1367
Category: Book
Authors: David S. Moore, George P. Mccabe
Publisher: W. H. Freeman
Studio: W. H. Freeman
Manufacturer: W. H. Freeman
Label: W. H. Freeman
Languages: English (Original Language), English (Unknown), English (Published)
Media: Hardcover
Edition: 5th
Number Of Items: 1
Pages: 896
Shipping Weight (lbs): 4.1
Dimensions (in): 10.1 x 8.2 x 1.5
ISBN: 0716764008
Dewey Decimal Number: 371
EAN: 9780716764007
ASIN: 0716764008
Publication Date: February 1, 2005
Availability: Usually ships in 1-2 business days
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Product Description
With its focus on data analysis, statistical reasoning, and the way statisticians actually work, Introduction to the Practice of Statistics (IPS) helped bring the power of critical thinking and practical applications to today's statistics classroom. Unlike more traditional ?plug and chug? /formula driven texts, IPS de-emphasizes probability and gives students a deeper understanding of statistics.
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| Customer Reviews: Read 9 more reviews...
Strengths and Weaknesses, But Still Among the Best Options September 8, 2008
I have taught an introductory statistics class for psychology majors at a big-10 school more often than I care to remember, using this edition of Moore and McCabe.
Although the book has a number of shortcomings (more on those later), it also has its advantages:
1) Given the age and popularity of this text, it can be easily and cheaply bought used.
2) This is book written at a level that is accessible to undergraduate students, even those whose mathematics background is lacking
3) The layout of the book is clear (unlike the next edition, the problems are not scattered all over the chapter). The review at the end of each section is helpful for students
4) Each section has a large variety of problems, both problems that can be solved by hand and problems that are best solved using software (data sets are usually included on the student CD-ROM)
5) The "extra" chapters on the CD-ROM are well-written. A honors or "advanced" course in introductory undergraduate statistics can easily be based on all the chapters in the (hardcopy) textbook and a chapter of one's own choice (e.g. Logistic Regression) from the CD.
6) The CD-ROM includes Power Point slides which can be used by students who prefer this format to my lectures (which are chalkboard-based)
7) A number of companion books, the most useful being the Excel and SPSS manuals are available.
8) A course website package for the compass system exists. This can provide weekly online multiple-choice quizzes, grade reporting features as well as an easy way to share files with students.
Some disadvantages of this textbook are:
1) Some data sets that should be on the student CD are mysteriously missing
2) The EESEE database with case studies' interface is very badly designed; some data sets are missing; students find it hard to import the existing data sets into statistical software.
3) Most formulae are simply stated without any proof. While this does alleviate the fears of some of the less-than-gifted students, it makes the course less enlightening for students who come into the course adequately prepared and motivated.
4) The books' focus on the standard deviation over the variance is sometimes a little extreme, especially in the section on the rules of Expectations and Variances.
5) The section on expectations and variances should be split into separate sections for continuous and discrete random variables; this might help some of the more confused students.
6) The chapter on 1-way ANOVA does not include the expectations of the mean squares or any information on the regression model for ANOVA. Furthermore, Bonferroni is the only method of correcting for type-I error that is discussed. Others could have at least been listed.
7) The chapter on 2-way ANOVA should be expanded. The authors do not mention that they are talking solely about fixed-effects 2-way ANOVA, do not provided the formulae for the mean squares (or their expectations) and do not explain 2-way ANOVA as a multiple regression model. This is somewhat mitigated by the fact that a regular class (i.e. not an honours class) will probably not be able to cover all 12 chapters prior to the 2-way ANOVA chapter (and thus this chapter is not used either).
I have investigated the possibility of using a different textbook, but have not found a replacement that has the strengths of this book without the weaknesses.
I would recommend this book for an elementary introduction to statistics for undergraduates course in the social sciences with the caveat that the instructor will have to supplement certain sections for those students who are intelligent, well-prepared and motivated.
 A great book with a very down to earth approach to statistical inference August 5, 2008
There are many statistics books out there, but this one really stands out. The style is extremely clear, the examples pertinent and the author constantly brings the reader to the basics, no non-sense, showing why and how particular items are important. Practitioners will find this book especially useful since it deals mainly with statistical inference (tests) and gives a great amount of real life examples.
The experienced statistician should stay away (if looking for an advanced textbook) since this book does not go into deep mathematical or theoretical details (the necessary minimum is provided).
A quick peek at the toc gives a reliable idea of its content.
 Sent extremely late July 30, 2008
0 out of 2 found this review helpful
I ordered this book for a summer school class, and it was not even sent out until three weeks after I ordered it. I received the book five weeks after I orginally ordered it, and two weeks too late for my class. I was and still am very annoyed by the seller.
Truly awful statistics textbook July 15, 2008
1 out of 2 found this review helpful
I never understood why this textbook has enjoyed such enduring popularity. This book presents statistics as nothing more than one formula after another, rarely stopping to justify any of them, and when it does try to explain something, it inevitably resorts to long and convoluted exposition. This is my main gripe with this textbook -- there is too much text and not enough math. I realize that this book is not concerned with the theoretical aspects of statistics, but in order to understand and apply statistics at even the most basic level, a certain facility with math is necessary. This book does its utmost to strip statistics of math, replacing it with long-winded verbal explanations wherever possible. Thus the book ends up being twice as long than perhaps it needs to be. (I've seen other introductory stat textbooks that cover everything in this textbook and more in 500 pages or less.)
I realize that many students taking introductory statistics are averse to math. But by replacing the math with exposition, this book does statistics a great disservice. Many people enjoy reading long-winded 1000-page novels because there is often good prose and a good story to be had; long-winded 1000-page statistics textbooks, on the other hand, are a chore for anybody to read because -- let's face it -- it just isn't possible to talk about sampling distributions like Tolstoy tells Anna Karenina. (Disclaimer: Sampling distributions can be every bit as exciting as Tolstoy, but it usually isn't much fun to read about them!) When books like these try to teach statistics as if it were a narrative, is it any wonder that so many students claim to find statistics boring?
One thing that this book does well is deceive readers into thinking that they know statistics, but it only breeds more confusion and misconceptions that will hurt students if they ever take another statistics class. For example, the book presents the concept of normal distributions before it even mentions probability. I suppose students enjoy seeing this topic early in the course because they've heard of the normal distribution and associate statistics with it. But the normal distribution is fundamentally a phenomenon of probability, and it applies to data only insofar as it is one of the many probability models for distribution of a given set of data. Yet students are asked to find normal probabilities before they are even introduced to what probability is. The statistics department at my school has griped that the students don't understand the difference between probability distribution and distribution of a set of data. Maybe students wouldn't have this problem if the intro classes didn't use a textbook that blurs the distinction between the two! In my own experience teaching with this text, I have encountered another fundamental misunderstanding that stems from introducing normal distributions so early on -- some students start calling ANY bell-shaped and symmetric distribution "normal."
As if that were not enough, the book neglects to mention one of the most important distinctions in all of probability/statistics -- that of discrete vs. continuous random variables. How are students supposed to understand what it means for a random variable to be normally distributed when everything they have studied about random variables has been discrete?
To compound the lousy presentation of material, the authors have somehow managed to come up with the least interesting problems possible for the exercises. Whereas most statistics textbooks select their data sets from actual experiments and studies, it really seems in some of the exercises that the authors fabricated a bunch of numbers for students to punch into their calculator/MiniTab.
If you are a professor or AP Stats teacher, please do your students a favor and look elsewhere for a suitable textbook. In my experience, McClave/Sincich treats statistics correctly (with separate chapters for discrete and continuous random variables!) and has interesting problems to boot. But my experience with statistics textbooks is limited, and there may be better books out there. Shop around, but chances are that you won't find a worse textbook than this one. If you are a student, you have my sympathies. Good luck working with this textbook, and don't feel bad if statistics makes less sense after reading this textbook than before.
another well-written and popular text by David Moore March 30, 2008
24 out of 24 found this review helpful
David Moore is a Professor of Statistics at Purdue University. He is both a great teacjer and a scholar. In addition to one or two well-written advanced books he has written a number of high quality introductory statistics books and has led the movement toward AP statistics in the high schools and active learning methods for tesching statistics at the elementary, middle and high school levels as well as at the universities.
This book is a new edition of his highly successful introductory text. This is only slightly more advanced than the text "The Basic Practice of Statistics" also written by Moore. This edition can only be as good or better than the one U have read. The inclusion of a CD for use in the course can only be a significant edition to this applied text.
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