This comprehensive and uniquely organized text is aimed at undergraduate and graduate level statistics courses in education and psychology. An organization scheme built around common issues and problems rather than statistical techniques allows students to understand the conceptual nature of statistical procedures. Likewise, it is so comprehensive and clearly written that instructors are freed from a considerable amount of didactic presentation thus allowing them to engage more with cases and examples of analysis. Whenever possible, presentations contain explanations of the underlying reasons…mehr
This comprehensive and uniquely organized text is aimed at undergraduate and graduate level statistics courses in education and psychology. An organization scheme built around common issues and problems rather than statistical techniques allows students to understand the conceptual nature of statistical procedures. Likewise, it is so comprehensive and clearly written that instructors are freed from a considerable amount of didactic presentation thus allowing them to engage more with cases and examples of analysis. Whenever possible, presentations contain explanations of the underlying reasons behind a technique. For example, nearly all introductory texts specify that when doing chi-squared tests on count data, expected cell frequencies should be five or more but most don't tell why. This text does.
William B. Ware is Professor at the University of North Carolina at Chapel Hill, USA. John M. Ferron is Professor at the University of South Florida, USA. Barbara M. Miller is Associate Professor at Elon University, USA.
Inhaltsangabe
1. Introduction and Background II. Descriptive Statistics 2. Describing Quantitative Data with Frequency Distributions 3. Describing Quantitative Data: Summary Statistics 4. Describing Categorical Data: Frequency Distributions, Graphics, and Summary Statistics 5. Describing the Position of a Case within a Set of Scores 6. Describing the Relationship between Two Quantitative Variables: Correlation 7. Describing the Relationship between Two Quantitative Variables: Regression III. The Fundamentals of Statistical Inference 8. The Essentials of Probability 9. Probability and Sampling Distributions 10. The Normal Distribution IV. Statistical Inference 11. The Basics of Statistical Inference: Tests of Location 12. Other One-Sample Tests for Location 13. More One-Sample Tests 14. Two-Sample Tests of Location 15. Other Two-Sample Tests: Variability and Relationships V. K-Sample Tests 16. Tests on Location: Analysis of Variance and Other Selected Procedures 17. Multiple Comparison Procedures 18. Looking Back... and Beyond Appendix A: Statistical Tables Appendix B: Getting Started with R Index
1. Introduction and Background II. Descriptive Statistics 2. Describing Quantitative Data with Frequency Distributions 3. Describing Quantitative Data: Summary Statistics 4. Describing Categorical Data: Frequency Distributions, Graphics, and Summary Statistics 5. Describing the Position of a Case within a Set of Scores 6. Describing the Relationship between Two Quantitative Variables: Correlation 7. Describing the Relationship between Two Quantitative Variables: Regression III. The Fundamentals of Statistical Inference 8. The Essentials of Probability 9. Probability and Sampling Distributions 10. The Normal Distribution IV. Statistical Inference 11. The Basics of Statistical Inference: Tests of Location 12. Other One-Sample Tests for Location 13. More One-Sample Tests 14. Two-Sample Tests of Location 15. Other Two-Sample Tests: Variability and Relationships V. K-Sample Tests 16. Tests on Location: Analysis of Variance and Other Selected Procedures 17. Multiple Comparison Procedures 18. Looking Back... and Beyond Appendix A: Statistical Tables Appendix B: Getting Started with R Index
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