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

Applied Statistics

Analysis of Variance and Regression

• Gebundenes Buch

Produktbeschreibung

This new edition of this standard has been extensively revised to serve the ever-increasing number of investigators who, with only a year or so of statistical training, are performing sophisticated statistical analyses on computers. It provides sound statistical methodology, practical advice on the application of this methodology, and information relating the statistics to computer manipulation and output.

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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.

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Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.

Produktdetails

• Wiley Series in Probability and Statistics
• Verlag: Wiley & Sons
• 3. Aufl.
• Seitenzahl: 448
• Erscheinungstermin: 6. Februar 2004
• Englisch
• Abmessung: 240mm x 161mm x 30mm
• Gewicht: 790g
• ISBN-13: 9780471370383
• ISBN-10: 047137038X
• Artikelnr.: 12347291

Autorenporträt

RUTH M. MICKEY, PHD, is Professor of Statistics at the University of Vermont in Burlington. OLIVE JEAN DUNN, PHD, is Professor Emeritus at the University of California, Los Angeles. VIRGINIA A. CLARK, PHD, is also Professor Emeritus at the University of California, Los Angeles. Drs. Dunn and Clark are the authors of Basic Statistics: A Primer for Biomedical Sciences, Third Edition, published by Wiley.

Inhaltsangabe

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.

Rezensionen

"...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)