Linear Models in Statistics (Wiley Series in Probability and Statistics) - Hardcover

Rencher, Alvin C.

 
9780471315643: Linear Models in Statistics (Wiley Series in Probability and Statistics)
Hardcover
ISBN 10: 0471315648 ISBN 13: 9780471315643
Publisher: Wiley–Blackwell, 1999

Synopsis

Linear models made easy with this unique introduction Linear Models in Statistics discusses classical linear models from a matrix algebra perspective, making the subject easily accessible to readers encountering linear models for the first time. It provides a solid foundation from which to explore the literature and interpret correctly the output of computer packages, and brings together a number of approaches to regression and analysis of variance that more experienced practitioners will also benefit from. With an emphasis on broad coverage of essential topics, Linear Models in Statistics carefully develops the basic theory of regression and analysis of variance, illustrating it with examples from a wide range of disciplines. Other features of this remarkable work include: Easy-to-read proofs and clear explanations of concepts and procedures Special topics such as multiple regression with random x's and the effect of each variable on R 2 Advanced topics such as mixed and generalized linear models as well as logistic and nonlinear regression The use of real data sets in examples, with all data sets available over the Internet Numerous theoretical and applied problems, with answers in an appendix A thorough review of the requisite matrix algebra Graphs, charts, and tables as well as extensive references

"synopsis" may belong to another edition of this title.

About the Author

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.

From the Back Cover

Linear models made easy with this unique introduction Linear Models in Statistics discusses classical linear models from a matrix algebra perspective, making the subject easily accessible to readers encountering linear models for the first time. It provides a solid foundation from which to explore the literature and interpret correctly the output of computer packages, and brings together a number of approaches to regression and analysis of variance that more experienced practitioners will also benefit from. With an emphasis on broad coverage of essential topics, Linear Models in Statistics carefully develops the basic theory of regression and analysis of variance, illustrating it with examples from a wide range of disciplines. Other features of this remarkable work include:*Easy-to-read proofs and clear explanations of concepts and procedures*Special topics such as multiple regression with random x's and the effect of each variable on R2*Advanced topics such as mixed and generalized linear models as well as logistic and nonlinear regression*The use of real data sets in examples, with all data sets available over the Internet*Numerous theoretical and applied problems, with answers in an appendix*A thorough review of the requisite matrix algebra*Graphs, charts, and tables as well as extensive references

"About this title" may belong to another edition of this title.

Publisher
Wiley–Blackwell
Publication date
1999
Language
English
ISBN 10 
0471315648
ISBN 13 
9780471315643
Binding
Hardcover
Number of pages
600

Other Popular Editions of the Same Title

9780471754985: Linear Models in Statistics

Featured Edition

ISBN 10:  0471754986 ISBN 13:  9780471754985
Publisher: Wiley-Interscience, 2008
Hardcover