Linear Models in Statistics
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- Wiley
More About This Title Linear Models in Statistics
English
ALVIN C. RENCHER, PhD, is Professor of Statistics at Brigham Young University and a Fellow of the American Statistical Association. He is the author of Methods of Multivariate Analysis and Multivariate Statistical Inference and Applications, both available from Wiley.
English
Matrix Algebra.
Random Vectors and Matrices.
Multivariate Normal Distribution.
Distribution of Quadratic Forms in y.
Simple Linear Regression.
Multiple Regression: Estimation.
Multiple Regression: Tests of Hypotheses and Confidence Intervals.
Multiple Regression: Model Validation and Diagnostics.
Multiple Regression: Random x's.
Analysis of Variance Models.
One-Way Analysis of Variance: Balanced Case.
Two-Way Analysis of Variance: Balanced Case.
Analysis of Variance: Unbalanced Data.
Analysis of Covariance.
Random Effects Models and Mixed Effects Models.
Additional Models.
Answers and Hints to Selected Problems.
Data Sets and SAS Files.
Bibliography.
Random Vectors and Matrices.
Multivariate Normal Distribution.
Distribution of Quadratic Forms in y.
Simple Linear Regression.
Multiple Regression: Estimation.
Multiple Regression: Tests of Hypotheses and Confidence Intervals.
Multiple Regression: Model Validation and Diagnostics.
Multiple Regression: Random x's.
Analysis of Variance Models.
One-Way Analysis of Variance: Balanced Case.
Two-Way Analysis of Variance: Balanced Case.
Analysis of Variance: Unbalanced Data.
Analysis of Covariance.
Random Effects Models and Mixed Effects Models.
Additional Models.
Answers and Hints to Selected Problems.
Data Sets and SAS Files.
Bibliography.
English
"Rencher...offers a textbook for a one-semester advanced undergraduate or beginning graduate course.... He includes more material than can actually squeeze into one semester...a good idea in statistics." (SciTech Book News, Vol. 24, No. 4, December 2000)
"An excellent book. Highly recommended. Upper-division undergraduate and graduate students; professionals." (Choice, Vol. 38, No. 7, March 2001)
"I would recommend the book to anyone as a reference book for the topics covered.... The book should also be a strong candidate for any M.S. course in linear models because of the numerous exercises with solutions and clear writing style." (Technometrics, Vol. 42, No. 4, May 2001)
"Rencher's textbook is certainly of interest for students and instructors looking for a mathematical introduction to linear statistical models." (Statistics & Decisions, Volume 19, No 2, 2001)
"...courses that go by the name "linear models" cover a combination of linear model theory, regression diagnostic, analysis of variance and more complex models that use linear models as a stepping stone. This book is appropriate for such courses...the collection of exercises adds to the book's value as a textbook." (Journal of the American Statistical Association, September 2001)
"Gives a solid theoretical foundation to standard topics..." (American Mathematical Monthly, November 2001)
"An excellent book. Highly recommended. Upper-division undergraduate and graduate students; professionals." (Choice, Vol. 38, No. 7, March 2001)
"I would recommend the book to anyone as a reference book for the topics covered.... The book should also be a strong candidate for any M.S. course in linear models because of the numerous exercises with solutions and clear writing style." (Technometrics, Vol. 42, No. 4, May 2001)
"Rencher's textbook is certainly of interest for students and instructors looking for a mathematical introduction to linear statistical models." (Statistics & Decisions, Volume 19, No 2, 2001)
"...courses that go by the name "linear models" cover a combination of linear model theory, regression diagnostic, analysis of variance and more complex models that use linear models as a stepping stone. This book is appropriate for such courses...the collection of exercises adds to the book's value as a textbook." (Journal of the American Statistical Association, September 2001)
"Gives a solid theoretical foundation to standard topics..." (American Mathematical Monthly, November 2001)
