Description 
1 online resource (xiii, 273 pages) : illustrations 
Contents 
Introduction  Principles of statistics  Introduction to linear regression  Assessing the regression  Multiple linear regression  Indicators, interactions, and transformations  Nonparametric statistics  Logistic regression  Diagnostics for logistic regression  Poisson regression  Survival analysis  Proportional hazards regression  Review of methods  Appendix: statistical tables 
Summary 
"This textbook for a second course in basic statistics for undergraduates or firstyear graduate students introduces linear regression models and describes other linear models including Poisson regression, logistic regression, proportional hazards regression, and nonparametric regression. Numerous examples drawn from the news and current events with an emphasis on health issues illustrate these concepts. Assuming only a precalculus background, the author keeps equations to a minimum and demonstrates all computations using SAS. Most of the programs and output are displayed in a selfcontained way, with an emphasis on the interpretation of the output in terms of how it relates to the motivating example. Plenty of exercises conclude every chapter. All of the datasets and SAS programs are available from the book's Web site, along with other ancillary material"Provided by publisher 
Bibliography 
Includes bibliographical references and index 
Notes 
Print version record 
Subject 
Linear models (Statistics)


Regression analysis.


SAS (Computer program language)

Form 
Electronic book

ISBN 
0511773706 (ebook) 

0511774761 (eBook) 

0511776284 (electronic bk.) 

0511778643 (electronic bk.) 

6612657936 

9780511773709 (ebook) 

9780511774768 (eBook) 

9780511776281 (electronic bk.) 

9780511778643 (electronic bk.) 

9786612657931 

(hardback) 

(hardback) 
