Data analysis and interpretation in the behavioral sciences
著者
書誌事項
Data analysis and interpretation in the behavioral sciences
Thomson/Wadsworth, c2003
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注記
Includes bibliographical references (p. [513]-515) and index
内容説明・目次
内容説明
Zechmeister and Posavac's unique, progressive pedagogical framework presents students with a model of analysis and interpretation called "I-D-E-A". This cutting edge model leads students through the processes of data inspection (I), description (D), estimating (E) confidence in their results, and announcing (A) their findings. Their friendly writing style and systematic approach to statistics involves the student in the topics presented. The authors stress the important first stage of data inspection and also demonstrate how both confidence intervals and effect sizes are complementary to traditional null hypothesis testing. Throughout the book, the authors emphasize the understanding and interpretation of statistics and place less emphasis on computation, acknowledging and encouraging computer-assisted data analysis. Concrete examples at the beginning of each chapter illustrate the kinds of questions and data that will be considered in that section. Having this variety of examples increases the likelihood that a student will relate to at least one of them.
Scenarios presented at the beginning of the chapter, which are referred to throughout the chapter so students can see how an example is affected by different stages of analysis and interpretation.
目次
Preface. 1. Introduction to the I-D-E-A Model of Data Analysis and Interpretation. Part 1: INSPECTING AND DESCRIBING DATA FROM ONE GROUP. 2. Inspecting Data Point by Point. 3. Inspecting Distributions of Data. 4. Describing Data from One Group. Part 2: I-D-E-A FOR A STUDY INVOLVING A SINGLE MEAN. 5. Estimating Confidence in a Mean. 6. Constructing a Confidence Interval and Announcing Results. Part 3: I-D-E-A WHEN THERE ARE TWO MEANS. 7. Inspecting and Describing Data When Comparing Two Means. 8. Estimating Using Confidence Intervals. 9. Estimating Using Null Hypothesis Significance Testing. 10. Interpreting and Announcing Results. Part 4: I-D-E-A WHEN THERE ARE MORE THAN TWO MEANS. 11. Inspecting, Describing, and Estimating Using Confidence Intervals. 12. Estimating Confidence Using Null Hypothesis Significance Testing, and Announcing Results. 13. I-D-E-A for Complex Designs. Part 5: I-D-E-A WHEN EXAMINING THE RELATIONSHIP BETWEEN TWO VARIABLES. 14. Inspecting and Describing Correlational Data. 15. Estimating Confidence Using Confidence Intervals. 16. Estimating Confidence Using Null Hypothesis Significance Testing, and Announcing Results. 17. Making Predictions. Part 6: I-D-E-A FOR STUDIES WITH NOMINAL DATA. 18. I-D-E-A with Nominal Data. Appendix A: Proportions of Area Under the Standard Normal Curve. Critical Values of t. Critical Values of F. Transformation of r to Zr. Critical Values of r. Critical Values of Chi Square (X2). Appendix B. A Brief Introduction to Power Analysis.
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