Nelson Higher Education

Higher Education

Learning SAS in the Computer Lab, 3rd Edition

  • Rebecca J. Elliott
  • Christopher H. Morrell
  • ISBN-10: 0495559687
  • ISBN-13: 9780495559689
  • 320 Pages | Paperback
  • Previous Editions: 2000, 1995
  • COPYRIGHT: 2010 Published
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Overview

About the Product

LEARNING SAS IN THE COMPUTER LAB, 3RD EDITION, gets students up and running quickly with SAS. Explaining concepts and commands in clear steps, the authors provide SAS basics so students can successfully apply computing techniques to all types of statistics problems and acquire an appreciation of data analysis. This brief, affordable manual also ensures that students learn enough about programming with SAS to be able to find their way around the many SAS reference manuals that they will use in their professional activities.

Features

  • Modular—Instructors can easily emphasize different points in statistics as appropriate for their courses. The 25 modules can be used in almost any order and the book works well with any introductory statistics text; students do not need to know calculus.

  • Realistic—Each module contains several problems that ask students to write a SAS program to analyze a set of data. Nearly all of the data sets (many collected by students for a statistics class) are real, enabling students to understand the connection of the material to the real world. Data sets are described in the Appendix; files can be found on the Book Companion Website.

  • Clear explanations with visuals—Each of 25 modules contains explanations of the appropriate SAS code and tips on what to look for on the output SAS generates. Examples of input and output let students see what data looks like in SAS. In addition, a tear-out road map (flowchart) at the back of the book explains which SAS procedures to use for different kinds of statistical analysis.

  • Flexible—The material can be used in a lab session or as a self-study aid for learning SAS.

About the Author

Rebecca J. Elliott

Rebecca Elliott has a Masters Degree in Statistics from Purdue University. She began her career with General Motors, supporting Current Product Manufacturing. She moved to Salt Lake City where she taught statistics at the University of Utah and developed the precursor to Learning SAS in the Computer Lab. She spent one year working for a survey research firm. She also provided statistical support through independent consulting. A native Hoosier, she has worked in Indianapolis for the past 10 years in the pharmaceutical industry supporting the manufacture of injectible drugs. Rebecca enjoys hiking in the desert, creating art with fabric, rooting for her team the WNBA Indiana Fever, traveling to sunny spots, and being on a spiritual path.

Christopher H. Morrell

Born in Cape Town, South Africa, Christopher Morrell obtained a bachelor’s degree at the University of Cape Town and a Ph.D. in statistics from the University of Wisconsin-Madison. Since then he has been a member of the Mathematical Sciences Department at Loyola College in Maryland, and teaches various undergraduate statistics courses. In addition, he was chair of the department from 2000 through 2006. Professor Morrell’s research involves statistical models that are used to describe repeated observations from longitudinal studies of aging. His statistical work has appeared in Journal of the American Statistical Association, Biometrics, Technometrics, Journal of the Royal Statistical Society: Series A & C, The American Statistician, Statistics in Medicine, and Communications in Statistics. He is also a co-author (with colleagues from the National Institute on Aging) on research that has appeared in numerous medical journals.

Table of Contents

1. THE BASICS.
Data Set Structure. Data Steps and PROC Steps. The Data Step. PROC PRINT. The Input Statement. Comparison of Character Formats. SAS Program, Log, and List Files. Problems.
2. MORE SAS BASICS.
Subsetting If. If. . . Then . . . Else Statements. PROC FORMAT. Subsetting Where. Using Data from Outside Files. Missover Option on Infile Statement. PROC IMPORT for Microsoft® Excel Files. PROC SORT. Set Statement. Problems.
3. DATA MANAGEMENT.
How SAS “Thinks.” Lag Function. Drop and Keep Statements. Combining Data Sets. Comment Lines. Limiting the Number of Observations Read from External Files. Setting the Size of the Output. The Put Statement. PROC EXPORT for Microsoft Excel Files. Problems.
4. SAS FUNCTIONS.
Numeric Functions. Character Functions. Probability Functions. Descriptive Statistics Functions. Problems.
5. DESCRIPTIVE STATISTICS I.
Label Statements. Title Statements. PROC UNIVARIATE. PROC BOXPLOT. Problems.
6. PROC GCHART.
PROC GCHART. Problems.
7. DESCRIPTIVE STATISTICS II.
PROC MEANS. PROC FREQ. Problems.
8. GENERATING RANDOM OBSERVATIONS.
SAS Distributional Functions. Do Loops. Problems.
9. X-Y PLOTS.
PROC GPLOT. Problems.
10. ONE-SAMPLE TESTS FOR µ, P.
One-Sample t-Tests. One-Sample Test for P. Problems.
11. TWO-SAMPLE T-TESTS.
PROC TTEST. T-Tests: Two-Sample, Pooled, and Paired. Problems.
12. ONE-WAY ANOVA.
Analysis of Variance—PROC GLM and PROC ANOVA. Problems.
13. TWO-WAY ANOVA AND MORE.
Two-Way ANOVA. General ANOVA Analysis. Problems.
14. MODEL CHECKING IN ANOVA.
Plots for Model Checking. More on PROC GLM. Problems.
15. CORRELATIONS.
PROC CORR. Problems.
16. SIMPLE LINEAR REGRESSION
PROC REG. Problems.
17. MODEL CHECKING IN REGRESSION.
Plots for Model Checking. More on PROC REG. Problems.
18. MULTIPLE LINEAR REGRESSION.
Multiple Regression. Problems.
19. MULTIPLE REGRESSION: AIDS FOR SELECTING AND ASSESSING MODELS.
Statistics Used in Multiple Regression Model Checking. PROC REG Selection = Option. Problems.
20. TESTS FOR CATEGORICAL DATA.
Chi-Square Tests. Problems.
21. NONPARAMETRIC TESTS.
One-Sample Tests. Tests for Two or More Samples. Problems.
22. ANALYSIS OF COVARIANCE.
Using PROC GLM for ANCOVA. Problems.
23. LOGISTIC REGRESSION
PROC LOGISTIC. Problems.
24. MATRIX COMPUTATIONS.
PROC IML. Problems.
25. MACRO VARIABLES AND PROGRAMS.
Macro Variables. Macro Programs. Problems.
DESCRIPTION OF DATA SETS.
INDEX.

New to this edition

  • Current – The new edition features code and graphics that are up-to-date with a more recent version of SAS while maintaining the book’s clear, accessible coverage of SAS basics.
  • New data sets and problems—Two data sets have been added; most modules have additional problems to provide students with ample opportunities to practice programming.
  • New modules—A new module covers matrix computations in SAS using IML; another new module introduces macro variables and macro programs.
  • Microsoft® Excel instructions—Instructions are now included on how to import/export data from and to Microsoft Excel.