Design and Analysis of Experiments
eBook - ePub

Design and Analysis of Experiments

Classical and Regression Approaches with SAS

  1. 856 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Design and Analysis of Experiments

Classical and Regression Approaches with SAS

About this book

Unlike other books on the modeling and analysis of experimental data, Design and Analysis of Experiments: Classical and Regression Approaches with SAS not only covers classical experimental design theory, it also explores regression approaches. Capitalizing on the availability of cutting-edge software, the author uses both manual meth

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Yes, you can access Design and Analysis of Experiments by Leonard C. Onyiah 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. Cover Page
  2. Halftitle Page
  3. Statistics: Textbooks and Monographs
  4. Statistics: Textbooks and Monographs
  5. Title Page
  6. Copyright Page
  7. Contents
  8. Preface
  9. Acknowledgments
  10. Author
  11. Chapter 1: Introductory Statistical Inference and Regression Analysis
  12. Chapter 2: Experiments, the Completely Randomized Design-Classical and Regression Approaches
  13. Chapter 3: Two-Factor Factorial Experiments and Repeated Measures Designs
  14. Chapter 4: Regression Approaches to the Analysis of Responses of Two-Factor Experiments and Repeated Measures Designs
  15. Chapter 5: Designs with Randomization Restriction-Randomized Complete Block, Latin Squares, and Related Designs
  16. Chapter 6: Regression Models for Randomized Complete Block, Latin Squares, and Graeco-Latin Square Designs
  17. Chapter 7: Factorial Designs—The 2k and 3k Factorial Designs
  18. Chapter 8: Regression Models for 2k and 3k Factorial Designs
  19. Chapter 9: Fractional Replication and Confounding in 2k and 3k Factorial Designs
  20. Chapter 10: Balanced Incomplete Blocks, Lattices, and Nested Designs
  21. Chapter 11: Methods for Fitting Response Surfaces and Analysis of Covariance
  22. Chapter 12: Multivariate Analysis of Variance (Manova)
  23. Appendix
  24. Index