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Data Analysis Using SAS - Peng, C. Y. Joanne

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        Avis sur Data Analysis Using Sas Format Broché  - Livre Science humaines et sociales, Lettres

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        Présentation Data Analysis Using Sas Format Broché

         - Livre Science humaines et sociales, Lettres

        Livre Science humaines et sociales, Lettres - Peng, C. Y. Joanne - 01/08/2008 - Broché - Langue : Anglais

        . .

      • Auteur(s) : Peng, C. Y. Joanne
      • Editeur : Sage Publications, Inc
      • Langue : Anglais
      • Parution : 01/08/2008
      • Format : Moyen, de 350g à 1kg
      • Nombre de pages : 640
      • Expédition : 1185
      • Dimensions : 25.4 x 17.8 x 3.4
      • ISBN : 1412956749



      • Résumé :
        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.

        Biographie:

        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.

        Sommaire:
        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

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