Data Analysis Using Sas

Peng, C. Y. Joanne

ISBN 10: 1412956749 / ISBN 13: 9781412956741

Editore: SAGE Publications, Inc, 2008

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Dati bibliografici

• Titolo: Data Analysis Using Sas
• Editore: SAGE Publications, Inc
• Data di pubblicazione: 2008
• Lingua: Inglese
• ISBN 10: 1412956749
• ISBN 13: 9781412956741
• Rilegatura: Brossura
• Condizione: As New

Descrizione articolo

Riassunto

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 at www.sagepub.com/pengstudy 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.

Informazioni sull?autore

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.