SAS Essentials: Co-author Alan C. Elliott on the latest edition of his book on mastering SAS for data analytics

Towards the end of last year, Wiley was proud to publish SAS Essentials: Mastering SAS for Data Analyticsa step-by-step introduction to using SAS statistical software as a foundational approach to data analysis and interpretation

Presenting a straightforward introduction from the ground up, SAS Essentials: Mastering SAS for Data Analytics, Second Edition illustrates SAS using hands-on learning techniques and numerous real-world examples. Keeping different experience levels in mind, the highly-qualified author team has developed the book over 20 years of teaching introductory SAS courses.

Divided into two sections, the first part of the book provides an introduction to data manipulation, statistical techniques, and the SAS programming language. The second section is designed to introduce users to statistical analysis using SAS Procedures. Featuring self-contained chapters to enhance the learning process, the Second Edition also includes:

  • Programming approaches for the most up-to-date version of the SAS platform including information on how to use the SAS University Edition
  • Discussions to illustrate the concepts and highlight key fundamental computational skills that are utilized by business, government, and organizations alike
  • New chapters on reporting results in tables and factor analysis
  • Additional information on the DATA step for data management with an emphasis on importing data from other sources, combining data sets, and data cleaning
  • Updated ANOVA and regression examples as well as other data analysis techniques
  • A companion website with the discussed data sets, additional code, and related PowerPoint slides

SAS Essentials: Mastering SAS for Data Analytics, Second Edition is an ideal textbook for upper-undergraduate and graduate-level courses in statistics, data analytics, applied SAS programming, and statistical computer applications as well as an excellent supplement for statistical methodology courses. The book is an appropriate reference for researchers and academicians who require a basic introduction to SAS for statistical analysis and for preparation for the Basic SAS Certification Exam.

Alison Oliver talks to co-author Alan C. Elliott about the new edition.

thumbnail image: SAS Essentials: Co-author Alan C. Elliott on the latest edition of his book on mastering SAS for data analytics

1. Congratulations to you and your co-author on the publication of your book, SAS Essentials, Mastering SAS for Data Analytics, Second Edition. How did the writing process begin?

Thanks! This book is the result of teaching Statistical Computing classes for over 20 years. The original courses included SAS, SPSS and other software. Later, the SAS class was separated into a single course. As the need and popularity of SAS has grown over the last 10 years, the classes became more comprehensive, and the course materials used in the course became more extensive. The original edition of SAS Essentials was a reworking of the original SAS class course manual. Since then we’ve continued to teach SAS while improving and expanding our examples and content. The second edition includes much of what we learned from our own teaching as well as input for other instructors who used the original book.

2. Who should read the book and why?

SAS Essentials is a ground-up introduction to SAS statistical software aimed at students taking an applied statistics course as well as individuals who want to learn SAS for personal use or to supplement preparation for the SAS Base Certification Exam. Originally the course was designed for students in a medical (mostly MDs) who were taking courses that led to a Masters in Clinical Research. Later the course was expanded to include students in the broader field of Data Analytics. Additional exercises and examples were added to cover topics in scientific research, business, and other fields of data analysis. Since many of the students were preparing to take the SAS Basic Certification exam, we included many of the programming topics that are covered in that exam. We also included examples from a number of statistical procedures (PROCS) for students using the text as a part of an applied statistics course. In general, we believe that the book is a valuable learning tool for anyone (in a classroom setting or not) who wants to learn SAS for data analytics. The book is written in a tutorial fashion with numerous hands-on examples that illustrate topics discussed. In this way, it can be used both as a textbook and as a personal learning guide.

3. The new edition also contains a multitude of exercises and examples are presented to illustrate each technique. SAS code and data used for the examples are available on the book’s supporting website. Was it always your objective to include a practical side to the book?

This book evolved out of the need for new SAS users to learn how to read data, manipulate it, and perform analyses. To that end, we do have extensive examples in every chapter. Because of the diversity of data sets and code samples needed to cover the broad range of topics, we’ve included all of the data files and SAS code files on the site. We also include PowerPoint slides for every chapter that can be used to teach the material. Plus, we’ve recently added a series of short videos that illustrate examples from the book. We continue to work to make the book as practical as possible by including these supplemental tools.

4. What is it about the area of data analysis that fascinates you?

Coming from a medial background, the use of data analysis to discover new treatments for diseases has always been fascinating to me. SAS is one tool that contributes to that process. An also in the age of big data, there is no better tool to read and summarize data (both in numbers and graphs) than SAS.

5. Why is this book still of particular interest?

We believe that data analytics will continue to be a growing field in business as well as in education and science, and that there will continue to be a need for people with the programming tools to help organizations understand this data, and to make decisions from it. SAS is the premiere tool to perform those analyses, and we believe this book provides the core knowledge that can help anyone in the data analytics field learn how to summarize data and use it from predictive analyses.

6. What were your main objectives during the writing process? What did you set out to achieve in reaching your readers?

This text is aimed at people who might have minimal (or no) programming experience. It starts at with the basics of how to use SAS and is designed to help student build confidence in their ability to program with SAS by teaching them programming skills one at a time, and that build on each other. Our experience is that students who follow these tutorial step-by-step examples can learn how to become a competent SAS programmer even if they have had minimal programming experience in the past. For people who already have programming skills, the material is still useful as it helps them discover how SAS reads, manipulates, and analyzes data.

7. Were there areas of the new edition that you found more challenging to write, and if so, why?

The book is split in to two parts. The first part is primarily about the SAS data step, and the second is primarily about analysis procedures (PROCS). One of the challenges in the first part was how to help students understand how to put together all of the individual programming components and create a full-blown SAS program that does a thorough job of cleaning up a typical data set. We did this by taking a messy data set, one with a lot of problems, and creating a step-by-step tutorial that walks the student through the discovery and correction of problems in the data set. This included case problems, missing values, data in incorrect format (such as dates), incorrectly coded data, and so on. At the end, the student sees a large program that contains a number of data correction procedures that is typical of a real-world data set clean-up.

8. Please could you tell us more about your educational background and what was it that brought you to recognize statistics as a discipline in the first place?

I was a resident biostatistician at the University of Texas, Southwestern Medical Center at Dallas for 30 years. I hold master’s degrees in business administration (MBA) and applied statistics (MAS) and have authored or coauthored a number of scientific articles and more than a dozen books on a wide variety of subjects including the Directory of Microcomputer Statistical SoftwareMicrocomputing with Applications, and the Statistical Analysis Quick Reference Guide. I have taught courses in statistics, research methods and computing (including SAS and SPSS) at the university for more than 20 years and has been a collaborator on numerous medical research projects. Currently I am the director of the Statistical Consulting Center at Southern Methodist University.

Wayne received his PhD (1974) in mathematical statistics from Texas Tech University. He is Professor of Statistics and Chair of the Department of Statistical Science at Southern Methodist University (SMU). He was elected as Fellow of the American Statistical Association in 1996 and in 2003 was named an Altshuler University Distinguished Teaching Professor at SMU. In 2004 he received the Don Owen Award, given annually by the San Antonio chapter of the American Statistical Association, for recognition of his contributions in the areas of research, consulting, and service to the statistical community. He was named the 2006–2007 United Methodist Church Scholar/Teacher of the Year at SMU. Wayne is an active researcher, having published more than 70 research articles. His primary research interests lie in the area of statistical time series analysis.