Customer Reviews

Applied Statistics and the SAS Programming Language (5th Edition)

5 star:		(22)
4 star:		(7)
3 star:		(4)
2 star:		(3)
1 star:		(4)

 

 

I've been doing data analysis for almost 20 years and recommend this highly. It is not too advanced for the beginning college student or professional, but more weighty than the small Introduction to SAS books (which seem more suitable for those with no experience). Because it interweaves SAS programming with often used statistics (and offers excellent examples and interpretations of output throughout), it is ideal for a stats and/or SAS course.

I find it useful for reviewing SAS steps, and as a quick stats overview. The big SAS books are fine as a reference or for researching more complex and/or narrower questions, but this is far more user-friendly. Highly recommended for the beginning to moderate statistician or programmer.

SAS is a data management and statistical analysis tool that is extremely popular in industry especially in medical device and pharmaceutical companies. SAS manuals are very good at providing users who have some statistical knowledge with guidance toward the use of various porcedures. Statistical texts often provide users of statistical methods with the necessary basic knowledge. However there are few texts that do both. A trend is developing to introduce basic and advanced statistical methods illustrated through the use of statistical software (particularly SAS). This book does a great job of presenting many applied problems and demonstrating the implementation of the analysis in SAS.

I just completed a SAS course that used this book. I never used SAS before and found the book to be very useful and informative. The authors show you how to use the built in SAS procedures and provide basic guidance on how to interpret the results. It has a numerous examples which really helped me learn the basics about running t-tests, ANOVA, and regression. Notes: (a) The book does not cover every option available with the SAS procedures - this is actually good in an introductory book because it keeps the reader from getting confused. Don't buy the book expecting a technical programming manual. (b) The book does not cover macro programming (c) the book does not cover the more professional looking graphics procedures e.g. gplot

This is an ideal book for a certain audience, and a good book for many audiences The ideal audience is college-level students or B.A. level professionals who know a little SAS and know a little statistics, and need to know how to combine them. The book is very clear and well organized, and makes no pretence to be what it isn't (i.e. a complete reference to SAS-STAT, a course book in statistics).

A good companion book would be DiIorio's SAS Applications Programming: A gentle introduction.

If you don't have the background of SAS programming. You should read this book. If you have the background of C/C++ and SQL, you will find SAS is very easy to learn.
I spend less time learning SAS concepts when I read this book. In part 1, the author reviews the basic concepts of statistics when running sas. This is very easy to understand!
In part 2, he mentions how to infile the large data in the sas environment. You don't have to type all the data in the sas enviroment in the beginning. It is very useful.
I think this is a good book for beginners who want to know what SAS programming is. I hope the author still can write the book about advanced SAS programming .

Once upon a time, I could not recommend this book highly enough. That's the problem--"once upon a time". In 2004, this book violates what I consider an overriding consideration for instruction books: Never distract the new user with picky details that s/he'll will rarely need in practice.

The first few chapters are written using INPUT and DATALINES; commands to enter data. For those unfamiliar with SAS, that means the authors enter all of their data as lines of text typed inside their command language. No one works that way any more! It's a hold over from the days of punchcards. Does the new user really need to know that
INPUT ID 1-3 AGE 4-5 GENDER $6;
means "look in columns 1-3 for a numerical id, columns 4-5 for numerical age, and column 6 for a character designating gender"? When the 4-th edition was written, the answer might have been yes, but even then it would have been given grudgingly. For more than a few years, data almost always arrive as data sets that have already been made into SAS files or as spreadsheets that can be imported directly into SAS. This method of data input would not be a fatal flaw if the material were in a later chapter or an appendix, but it's woven throughout the text starting with the first example on page 3.

I would love to see this book updated with a more modern view to how data are processed and analyzed, but I can no longer recommend it in its current form.

Added in edit: Instead, get a copy of "The Little SAS Book: A Primer, Third Edition" by Lora D. Delwiche and Susan J. Slaughter. If I ever get around to reviewing it, I'll give it 4 or 5 stars. In the meantime, there are already a bunch of reviews you can read on the book's own Amazon web page, mostly good, a few bad, for an average of 4 stars.

Cody and Smith do an effective job of communicating the intricacies and features of this helpful but sometimes dense software. A step-by-step, well organized and at times amusing approach to programming in SAS, this book is similar to the "..for dummies" collection - user-friendly with plenty of visuals and examples. I'd definitely recommend it to any student or professional.

I bought this book a few years ago, and still find myself referencing it more than any other book on the subject. It is a great book for those who use SAS, but do not use it daily. Cody and Smith have converted a difficult and dry subject into something that is as enjoyable to read as can be done given the subject matter. The authors do a fine job of explaining each process, when to use it, and how to interpret the results. Their examples are easy to understand, and the tips they provide are helpful. For instance, when talking about correlation, some other books fail to mention common mistakes made when doing the analysis, such as correlation not implying causality: this book clearly injects this in the chapter and gives a straightforward example to reinforce the point made.

It is an excellent reference manual and deserves a spot alongside your SAS manuals.

[A review of the 5th EDITION 2005.]

Cody and Smith refine their text on learning to program SAS. They assume you already know many statistical concepts, including skewness, kurtosis, Kolmogorov-Smirnov test and Student's T distribution. It is not a book on statistics per se, but how you can use SAS to compute these quantities from your input data.

There is no fancy GUI of graphs taught here. The style of the SAS outputs given in the book reflects in part a legacy of an earlier time when graphical options were very limited. But you need to realise that understanding how to program in SAS does not necessitate nifty graphics. In statistics, a lot of understanding still comes from looking at tabular results, and simple graphics like scatterplots. The book shows how to get such results displayed.

From the programming standpoint, the SAS language is pretty straightforward. Like writing script files. The main point is that the hard conceptual stuff is outside the book's remit. Instead, the book shows how SAS programming lets you handily access the large set of routines SAS has built, to do the tedious or complicated number crunching. It's up to you to decide what routines to use, and to understand the significance of the results.

This is a great book for people just starting to work with SAS or people who haven't done SAS in a while. It covers many basic analyses (maybe up to the second basic stats class in graduate school). The only bad thing about this text is that it doesn't cover enough of the multivariate techniques. Nonetheless, great step-by-step how-to for beginners. I highly recommend this text as an introduction or a refresher!