Applied Regression Analysis and Other Multivariable Methods
eBook - PDF

Applied Regression Analysis and Other Multivariable Methods

  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

Applied Regression Analysis and Other Multivariable Methods

About this book

This bestseller will help you learn regression-analysis methods that you can apply to real-life problems. It highlights the role of the computer in contemporary statistics with numerous printouts and exercises that you can solve using the computer. The authors continue to emphasize model development, the intuitive logic and assumptions that underlie the techniques covered, the purposes, advantages, and disadvantages of the techniques, and valid interpretations of those techniques. Available with InfoTrac® Student Collections http://gocengage.com/infotrac.

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Yes, you can access Applied Regression Analysis and Other Multivariable Methods by David Kleinbaum, Lawrence Kupper, Azhar Nizam, Eli Rosenberg in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Dedications
  2. Contents
  3. Preface
  4. Ch 1: Concepts and Examples of Research
  5. Ch 2: Classification of Variables and the Choice of Analysis
  6. Ch 3: Basic Statistics: A Review
  7. Ch 4: Introduction to Regression Analysis
  8. Ch 5: Straight-Line Regression Analysis
  9. Ch 6: The Correlation Coefficient and Straight-Line Regression Analysis
  10. Ch 7: The Analysis-of-Variance Table
  11. Ch 8: Multiple Regression Analysis: General Considerations
  12. Ch 9: Statistical Inference in Multiple Regression
  13. Ch 10: Correlations: Multiple, Partial, and Multiple Partial
  14. Ch 11: Confounding and Interaction in Regression
  15. Ch 12: Dummy Variables in Regression
  16. Ch 13: Analysis of Covariance and Other Methods for Adjusting Continuous Data
  17. Ch 14: Regression Diagnostics
  18. Ch 15: Polynomial Regression
  19. Ch 16: Selecting the Best Regression Equation
  20. Ch 17: One-Way Analysis of Variance
  21. Ch 18: Randomized Blocks: Special Case of Two-Way ANOVA
  22. Ch 19: Two-Way ANOVA with Equal Cell Numbers
  23. Ch 20: Two-Way ANOVA with Unequal Cell Numbers
  24. Ch 21: The Method of Maximum Likelihood
  25. Ch 22: Logistic Regression Analysis
  26. Ch 23: Polytomous and Ordinal Logistic Regression
  27. Ch 24: Poisson Regression Analysis
  28. Ch 25: Analysis of Correlated Data Part 1: The General Linear Mixed Model
  29. Ch 26: Analysis of Correlated Data Part 2: Random Effects and Other Issues
  30. Ch 27: Sample Size Planning for Linear and Logistic Regression and Analysis of Variance
  31. Appendix A: Tables
  32. Appendix B: Matrices and Their Relationship to Regression Analysis
  33. Appendix C: SAS Computer Appendix
  34. Appendix D: Answers to Selected Problems
  35. Index