Data Analysis Using SAS

Häftad, Engelska, 2008

Av Chao-Ying Joanne Peng, C. Y. Joanne Peng, C.Y. Joanne Peng

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Data Analysis Using SAS offers a comprehensive core text focused on key concepts and techniques in quantitative data analysis using the most current SAS commands and programming language. The coverage of the text is more evenly balanced among statistical analysis, SAS programming, and data/file management than any available text on the market. It provides students with a hands-on, exercise-heavy method for learning basic to intermediate SAS commands while understanding how to apply statistics and reasoning to real-world problems.

Designed to be used in order of teaching preference by instructor, the book is comprised of two primary sections: the first half of the text instructs students in techniques for data and file managements such as concatenating and merging files, conditional or repetitive processing of variables, and observations. The second half of the text goes into great depth on the most common statistical techniques and concepts - descriptive statistics, correlation, analysis of variance, and regression - used to analyze data in the social, behavioral, and health sciences using SAS commands. A student study comes replete with a multitude of computer programs, their output, specific details on how to check assumptions, as well as all data sets used in the book.

Data Analysis Using SAS is a complete resource for Data Analysis I and II, Statistics I and II, Quantitative Reasoning, and SAS Programming courses across the social and behavioral sciences and health - especially those that carry a lab component.

Produktinformation

Utgivningsdatum2008-10-23
Mått177 x 254 x 22 mm
Vikt1 080 g
FormatHäftad
SpråkEngelska
Antal sidor640
Upplaga1
FörlagSAGE Publications
ISBN9781412956741

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C.Y. Joanne Peng (PhD, University of Wisconsin-Madison, Quantitative Methodswith a minor in Statistics) is Professor of Educational Inquiry Methodology andAdjunct Professor of Statistics at IndianaUniversity. Her research interestsinclude logistic regression, missing data methods, and statistical computing usingSAS, SPSS, BMDP, Minitab, CLUSTAN, Systat, and S+. Shehas published more than 50 refereed articles, book chapters, technical reports,and encyclopedia entries on applied statistics, psychometrics, and statisticalcomputing. She is the author or co-author of two books on using SAS® forstatistical analyses and received one BEST PAPER Award at a SAS® users annualconference. She has taught applied statistics and data analysis coursesat major Research I universities for the past 20 years, including University of Wisconsin,University of Iowa,University of NorthCarolina, and IndianaUniversity. She is amember of the American Statistical Association, American Educational ResearchAssociation, American Psychological Association, and the SAS Users GroupInternational.

PART I. INTRODUCTION TO SAS AND BASIC DATA ANALYSIS1. Why do you need to learn SAS for data analyses?2. Where do you start?3. How to prepare data for SAS processing4. From data to a SAS data set5. Enhancing SAS programs and output6. Verifying data7. Data transformationPART II. STATISTICAL PROCEDURES8. Quick descriptive analysis9. Comprehensive descriptive analysis and normality test10.Graphing data11. Categorical data analysis12. T-test of population means13. Analysis of variance14. Inferences about two or more population typical scores by ranks15. Examining trends in data16. Correlation17. When do you stop worrying and start loving regression?PART III. ADVANCED DATA AND FILE MANAGEMENT18. Selecting variables or observations from a SAS data set19. Repetitive and conditional data processing20. Structuring SAS data setsAppendix A. What lies beyond this book? Information on reference books, hotlines, and Internet resourcesAppendix B. Data sets used in this bookAppendix C. Converting SPSS, STATA, Excel, Minitab, Systat data set files to SAS data sets or data set files

“Peng provides an excellent overview of data analysis using the powerful statistical software package SAS. This book is quite appropriate as a self-placed tutorial for researchers, as well as a textbook or supplemental workbook for data analysis courses such as statistics or research methods. Peng provides detailed coverage of SAS capabilities using step-by-step procedures and includes numerous comprehensive graphics and figures, as well as SAS printouts. Readers do not need a background in computer science or programming. Includes numerous examples in education, health sciences, and business.”