Signed-Rank Test
Program 12.5: Performing a Kruskal-Wallis ANOVA
Program 12.6: Performing the Ansari-Bradley Test for Spread
Program 12.7: Demonstrating PROC RANK
Program 12.8: Replacing Values with Ranks and Running a t-Test
Program 12.9: Using PROC RANK to Create Groups
Program 13.1: Computing Sample Size for an Unpaired t-Test
Program 13.2: Computing the Power of a t-Test
Program 13.3: Computing the Power for an ANOVA Design
Program 13.4: Computing Sample Size for a Difference in Two Proportions
Program 14.1: Taking a Simple Random Sample
Program 14.2: Taking a Random Sample with Replacement
Program 14.3: Rerunning the Program without the OUTHITS Option
Program 14.4: Requesting Replicate Samples
Acknowledgments
A tremendous amount of work went into bringing this book to the bookshelf, and all that work wasn’t done by me alone. Several factors combined to make the review process and the final production of this book a challenge.
First and foremost, I would like to thank John West, my editor and friend, who was amazingly patient and calm, even when there were technical challenges to overcome.
Next, we enlisted the help of more reviewers than usual. Four of these reviewers read the book from cover to cover and made excellent suggestions for improvements and found some subtle and obscure errors. So, kudos to Gerry Hobbs, Catherine Truxillo, Jeff Smith, and Marc Huber.
Other reviewers read chapters, particularly those where they had a particular expertise. Sincere thanks to Rob Agnelli, Paul Grant, Sanjay Matange, David Schlotzhauer, Jim Seabolt, and Sue Walsh.
Since the decision was made to use HTML output instead of simple list output, considerable extra effort was required. The production team needed to “touch” approximately 161 image files so that they would look good both in print as well as on the various eBook devices. The people involved in this process were: Jennifer Dilley, designer; Candy Farrell, technical publishing specialist; Joan Celmer, copyeditor; and Mary Beth Steinbach, managing editor.
No book would be successful without having people to market it. Thanks to Aimee Rodriguez and Stacey Hamilton for this essential task.
Finally, I salute the artists who created the front and back covers of the book. Nice job Jennifer Dilley and Marchellina Waugh.
Ron Cody, Summer 2011
Chapter 1 An Introduction to SAS
Statistical Tasks Performed by SAS
Variable Types in SAS Data Sets
Temporary versus Permanent SAS Data Sets
Creating a SAS Data Set from Raw Data
Data Values Separated by Delimiters
Excel Files with Invalid SAS Variable Names
Introduction
If you are reading this book, you are probably familiar with various statistical techniques but might not have used SAS to analyze data. The primary purpose of this book is to show you how to use SAS to perform a variety of statistical tasks. To that end, this book provides examples of many of the commonly used statistical techniques. Following each example is a discussion of the output. Although this is not a book about SAS programming, many of the examples require some data manipulation tasks, which will be described. If you need to gain more SAS programming skills, see Learning SAS by Example: A Programmer’s Guide, also by this author and published by SAS Press.
This book is divided into five sections: An Introduction to SAS, Descriptive Statistics, Inferential Statistics, Power/Sample size calculations, and Selecting Random Samples.
All of the programs and data files in this book are available from SAS Press. To download these programs and files, go to http://support.sas.com/authors.
If you already have some familiarity with SAS data sets and how to run SAS programs, you can skip this chapter and start right in with Chapter 2.
The remainder of this chapter describes what SAS is, the basic structure of SAS programs, how to access some simple data sets, and how to run a SAS program on a Windows platform.
What is SAS
SAS (pronounced sass) is a collection of programs that are used to read data from a variety of sources (text files, Excel workbooks, various databases, etc.), to manipulate data with a very powerful programming language,
