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THE STATISTICAL SLEUTH: A COURSE IN METHODS OF DATA ANALYSIS, Third Edition offers an appealing treatment of general statistical methods that takes full advantage of the computer, both as a computational and an analytical tool. The material is independent of any specific software package, and prominently treats modeling and interpretation in a way that goes beyond routine patterns. The book focuses on a serious analysis of real case studies, strategies and tools of modern statistical data analysis, the interplay of statistics and scientific learning, and the communication of results. With interesting examples, real data, and a variety of exercise types (conceptual, computational, and data problems), the authors get students excited about statistics.
- Real-world case studies introduce each method.
- Updated data problems cover current events, adding interest and relevance to the material.
- Problems are those graduate researchers typically encounter, with regression as the principal featured tool. Generalized linear models, repeated measures, and serial correlation are also included.
- The fundamentals of drawing sound inferences receive strong, early coverage in Chapters 1–4, introduced by means of two-sample problems.
- The book presents an excellent discussion of design issues (as they apply to case studies) throughout, and includes two experimental design chapters at the end of the book.
2. Inference Using t-Distributions.
3. A Closer Look at Assumptions.
4. Alternatives to the t-Tools.
5. Comparisons among Several Samples.
6. Linear Combinations and Multiple Comparisons of Means.
7. Simple Linear Regression: A Model for the Mean.
8. A Closer Look at Assumptions for Simple Linear Regression.
9. Multiple Regression.
10. Inferential Tools for Multiple Regression.
11. Model Checking and Refinement.
12. Strategies for Variable Selection.
13. The Analysis of Variance for Two-Way Classifications.
14. Multifactor Studies Without Replication.
15. Adjustment for Serial Correlation.
16. Repeated Measures and Other Multivariate Responses.
17. Exploratory Tools for Summarizing Multivariate Responses.
18. Comparisons of Proportions or Odds.
19. More Tools for Tables of Counts.
20. Logistics Regression for Binary Response Variables.
21. Logistic Regression for Binomial Counts.
22. Log-Linear Regression for Poisson Counts.
23. Elements of Research Design.
24. Factorial Treatment Arrangements and Blocking Designs.
Appendix A. Tables.
Appendix B. References.
Cengage provides a range of supplements that are updated in coordination with the main title selection. For more information about these supplements, contact your Learning Consultant.
Instructor's Solutions Manual
This online instructor database offers complete worked solutions to all exercises in the text, allowing you to create customized, secure solutions printouts (in PDF format) matched exactly to the problems you assign in class. Visit Cengage.com/solutionbuilder for more information.
Student Solutions Manual
This manual contains fully worked-out solutions to all of the odd-numbered exercises in the text, giving students a way to check their answers and ensure that they took the correct steps to arrive at an answer
Student Solutions Manual