Description

Book Synopsis
This work has been thoughtfully designed so that it serves equally well as a reference for the practitioner and as a self-contained textbook for the advanced student.
* Rewritten to maintain clarity and brevity while expanding the coverage of previous editions.
* Changes to design-related topics include increased discussion of mixed models and random effects, greater emphasis on regression and data screening, and more use of graphs throughout.
* Includes both graded and challenging exercises.
* Liberal computer discussions now supplemented with SAS and SPSS.

Trade Review
"…beginning level graduate students in statistics will find this book very valuable." (Journal of Statistical Computation and Simulation, January 2006)

"…Overall this is an excellent book…I recommend this book to everyone…" (Statistical Methods in Medical Research, Vol. 14, 2005)

"…The book is an excellent material for describing the data as well as a useful textbook for students to understand, apply and to interpret the statistical methods." (Zentralbaltt MATH, May 2005)

"…it contains a wealth of useful up-to-date information and examples from the health sciences." (Technometrics, November 2004)

"The level of the book is also more consistently intermediate...a few more advanced topics are now excluded." (The American Statistician, August 2004)



Table of Contents
Preface.

1. Data Screening.

Problems.

References.

2. One-Way Analysis of Variance Design.

Problems.

References.

3. Estimation and Simultaneous Inference.

Problems.

References.

4. Hierarchical or Nested Design.

Problems.

References.

5. Two Crossed Factors: Fixed Effects and Equal Sample Sizes.

Problems.

References.

6 Randomized Complete Block Design.

Problems.

References.

7. Two Crossed Factors: Fixed Effects and Unequal Sample Sizes.

Problems.

References.

8. Crossed Factors: Mixed Models.

Problems.

References.

9. Repeated Measures Designs.

Problems.

References.

10. Linear Regression: Fixed X Model.

Problems.

References.

11. Linear Regression: Random X Model and Correlation.

Problem.

References.

12. Multiple Regression.

Problems.

References.

13. Multiple and Partial Correlation.

Problems.

References.

14. Miscellaneous Topics in Regression.

Problems.

References.

15. Analysis of Covariance.

Problems.

References.

16. Summaries, Extensions, and Communication.

References.

Appendix A.

Appendix B.

Index.

Applied Statistics

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    A Hardback by Ruth M. Mickey, Olive Jean Dunn, Virginia A. Clark

      Trusted by thousands of customers. See 2,385+ Customer Reviews

      View other formats and editions of Applied Statistics by Ruth M. Mickey

      Publisher: John Wiley & Sons Inc
      Publication Date: 05/03/2004
      ISBN13: 9780471370383, 978-0471370383
      ISBN10: 047137038X
      Also in:
      Mathematics

      Description

      Book Synopsis
      This work has been thoughtfully designed so that it serves equally well as a reference for the practitioner and as a self-contained textbook for the advanced student.
      * Rewritten to maintain clarity and brevity while expanding the coverage of previous editions.
      * Changes to design-related topics include increased discussion of mixed models and random effects, greater emphasis on regression and data screening, and more use of graphs throughout.
      * Includes both graded and challenging exercises.
      * Liberal computer discussions now supplemented with SAS and SPSS.

      Trade Review
      "…beginning level graduate students in statistics will find this book very valuable." (Journal of Statistical Computation and Simulation, January 2006)

      "…Overall this is an excellent book…I recommend this book to everyone…" (Statistical Methods in Medical Research, Vol. 14, 2005)

      "…The book is an excellent material for describing the data as well as a useful textbook for students to understand, apply and to interpret the statistical methods." (Zentralbaltt MATH, May 2005)

      "…it contains a wealth of useful up-to-date information and examples from the health sciences." (Technometrics, November 2004)

      "The level of the book is also more consistently intermediate...a few more advanced topics are now excluded." (The American Statistician, August 2004)



      Table of Contents
      Preface.

      1. Data Screening.

      Problems.

      References.

      2. One-Way Analysis of Variance Design.

      Problems.

      References.

      3. Estimation and Simultaneous Inference.

      Problems.

      References.

      4. Hierarchical or Nested Design.

      Problems.

      References.

      5. Two Crossed Factors: Fixed Effects and Equal Sample Sizes.

      Problems.

      References.

      6 Randomized Complete Block Design.

      Problems.

      References.

      7. Two Crossed Factors: Fixed Effects and Unequal Sample Sizes.

      Problems.

      References.

      8. Crossed Factors: Mixed Models.

      Problems.

      References.

      9. Repeated Measures Designs.

      Problems.

      References.

      10. Linear Regression: Fixed X Model.

      Problems.

      References.

      11. Linear Regression: Random X Model and Correlation.

      Problem.

      References.

      12. Multiple Regression.

      Problems.

      References.

      13. Multiple and Partial Correlation.

      Problems.

      References.

      14. Miscellaneous Topics in Regression.

      Problems.

      References.

      15. Analysis of Covariance.

      Problems.

      References.

      16. Summaries, Extensions, and Communication.

      References.

      Appendix A.

      Appendix B.

      Index.

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