This comprehensive, flexible text is used in both one- and two-semester courses to review introductory through intermediate statistics. Instructors select the topics that are most appropriate for their course. Its conceptual approach helps students more easily understand the concepts and interpret SPSS and research results.
This comprehensive, flexible text is used in both one- and two-semester courses to review introductory through intermediate statistics. Instructors select the topics that are most appropriate for their course. Its conceptual approach helps students more easily understand the concepts and interpret SPSS and research results.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Debbie L. Hahs-Vaughn is Professor of Methodology, Measurement, and Analysis at the University of Central Florida, US. Her primary research interest relates to methodological issues associated with applying quantitative statistical methods to survey data obtained under complex sampling designs and using complex survey data to answer substantive research questions. Richard G. Lomax is Professor Emeritus of Educational and Human Ecology at the Ohio State University, US, and former Associate Dean for Research and Administration. His research primarily focuses on early literacy and statistics.
Inhaltsangabe
Preface Acknowledgements 1. INTRODUCTION 2. DATA REPRESENTATION 3. UNIVARIATE POPULATION PARAMETERS AND SAMPLE STATISTICS 4. THE NORMAL DISTRIBUTION AND STANDARD SCORES 5. INTRODUCTION TO PROBABILITY AND SAMPLE STATISTICS 6. INTRODUCTION TO HYPOTHESIS TESTING: INFERENCES ABOUT A SINGLE MEAN 7. INFERENCES ABOUT THE DIFFERENCE BETWEEN TWO MEANS 8. INFERENCES ABOUT PROPORTIONS 9. INFERENCES ABOUT VARIANCES 10. BIVARIATE MEASURES OF ASSOCIATION 11. ONE-FACTOR ANALYSIS OF VARIANCE - FIXED-EFFECTS MODEL 12. MULTIPLE COMPARISON PROCEDURES 13. FACTORIAL ANALYSIS OF VARIANCE - FIXED-EFFECTS MODEL 14. INTRODUCTION TO ANALYSIS OF COVARIANCE: THE ONE-FACTOR FIXED-EFFECTS MODEL WITH A SINGLE COVARIATE 15. RANDOM- AND MIXED-EFFECTS ANALYSIS OF VARIANCE MODELS 16. HIERARCHICAL AND RANDOMIZED BLOCK ANALYSIS OF VARIANCE MODELS 17. SIMPLE LINEAR REGRESSION 18. MULTIPLE LINEAR REGRESSION 19. LOGISTIC REGRESSION 20. MEDIATION AND MODERATION Appendix: Tables
Preface Acknowledgements 1. INTRODUCTION 2. DATA REPRESENTATION 3. UNIVARIATE POPULATION PARAMETERS AND SAMPLE STATISTICS 4. THE NORMAL DISTRIBUTION AND STANDARD SCORES 5. INTRODUCTION TO PROBABILITY AND SAMPLE STATISTICS 6. INTRODUCTION TO HYPOTHESIS TESTING: INFERENCES ABOUT A SINGLE MEAN 7. INFERENCES ABOUT THE DIFFERENCE BETWEEN TWO MEANS 8. INFERENCES ABOUT PROPORTIONS 9. INFERENCES ABOUT VARIANCES 10. BIVARIATE MEASURES OF ASSOCIATION 11. ONE-FACTOR ANALYSIS OF VARIANCE - FIXED-EFFECTS MODEL 12. MULTIPLE COMPARISON PROCEDURES 13. FACTORIAL ANALYSIS OF VARIANCE - FIXED-EFFECTS MODEL 14. INTRODUCTION TO ANALYSIS OF COVARIANCE: THE ONE-FACTOR FIXED-EFFECTS MODEL WITH A SINGLE COVARIATE 15. RANDOM- AND MIXED-EFFECTS ANALYSIS OF VARIANCE MODELS 16. HIERARCHICAL AND RANDOMIZED BLOCK ANALYSIS OF VARIANCE MODELS 17. SIMPLE LINEAR REGRESSION 18. MULTIPLE LINEAR REGRESSION 19. LOGISTIC REGRESSION 20. MEDIATION AND MODERATION Appendix: Tables
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