Data Analysis Using SAS
Autor C. Y. Joanne Pengen Limba Engleză Paperback – 28 aug 2008
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.
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Specificații
ISBN-13: 9781412956741
ISBN-10: 1412956749
Pagini: 640
Dimensiuni: 178 x 254 x 34 mm
Greutate: 1.19 kg
Ediția:1
Editura: Sage Publications, Inc
Locul publicării:Thousand Oaks, United States
ISBN-10: 1412956749
Pagini: 640
Dimensiuni: 178 x 254 x 34 mm
Greutate: 1.19 kg
Ediția:1
Editura: Sage Publications, Inc
Locul publicării:Thousand Oaks, United States
Recenzii
“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.”
Cuprins
PART I. INTRODUCTION TO SAS AND BASIC DATA ANALYSIS
1. Why do you need to learn SAS for data analyses?
2. Where do you start?
3. How to prepare data for SAS processing
4. From data to a SAS data set
5. Enhancing SAS programs and output
6. Verifying data
7. Data transformation
PART II. STATISTICAL PROCEDURES
8. Quick descriptive analysis
9. Comprehensive descriptive analysis and normality test
10.Graphing data
11. Categorical data analysis
12. T-test of population means
13. Analysis of variance
14. Inferences about two or more population typical scores by ranks
15. Examining trends in data
16. Correlation
17. When do you stop worrying and start loving regression?
PART III. ADVANCED DATA AND FILE MANAGEMENT
18. Selecting variables or observations from a SAS data set
19. Repetitive and conditional data processing
20. Structuring SAS data sets
Appendix A. What lies beyond this book? Information on reference books, hotlines, and Internet resources
Appendix B. Data sets used in this book
Appendix C. Converting SPSS, STATA, Excel, Minitab, Systat data set files to SAS data sets or data set files
1. Why do you need to learn SAS for data analyses?
2. Where do you start?
3. How to prepare data for SAS processing
4. From data to a SAS data set
5. Enhancing SAS programs and output
6. Verifying data
7. Data transformation
PART II. STATISTICAL PROCEDURES
8. Quick descriptive analysis
9. Comprehensive descriptive analysis and normality test
10.Graphing data
11. Categorical data analysis
12. T-test of population means
13. Analysis of variance
14. Inferences about two or more population typical scores by ranks
15. Examining trends in data
16. Correlation
17. When do you stop worrying and start loving regression?
PART III. ADVANCED DATA AND FILE MANAGEMENT
18. Selecting variables or observations from a SAS data set
19. Repetitive and conditional data processing
20. Structuring SAS data sets
Appendix A. What lies beyond this book? Information on reference books, hotlines, and Internet resources
Appendix B. Data sets used in this book
Appendix C. Converting SPSS, STATA, Excel, Minitab, Systat data set files to SAS data sets or data set files
Notă biografică
C.Y. Joanne Peng (PhD, University of Wisconsin-Madison, Quantitative Methods with a minor in Statistics) is Professor of Educational Inquiry Methodology and Adjunct Professor of Statistics at Indiana University. Her research interests include logistic regression, missing data methods, and statistical computing using SAS, SPSS, BMDP, Minitab, CLUSTAN, Systat, and S+. She has published more than 50 refereed articles, book chapters, technical reports, and encyclopedia entries on applied statistics, psychometrics, and statistical computing. She is the author or co-author of two books on using SAS® for statistical analyses and received one BEST PAPER Award at a SAS® users annual conference. She has taught applied statistics and data analysis courses at major Research I universities for the past 20 years, including University of Wisconsin, University of Iowa, University of North Carolina, and Indiana University. She is a member of the American Statistical Association, American Educational Research Association, American Psychological Association, and the SAS Users Group International.
Descriere
This book 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.