Master linear regression techniques with a new edition of a classic text
Reviews of the Second Edition:
"I found it enjoyable reading and so full of interesting material that even the well-informed reader will probably find something new . . . a necessity for all of those who do linear regression."
—Technometrics, February 1987
"Overall, I feel that the book is a valuable addition to the now considerable list of texts on applied linear regression. It should be a strong contender as the leading text for a first serious course in regression analysis."
—American Scientist, May–June 1987
Applied Linear Regression, Third Edition has been thoroughly updated to help students master the theory and applications of linear regression modeling. Focusing on model building, assessing fit and reliability, and drawing conclusions, the text demonstrates how to develop estimation, confidence, and testing procedures primarily through the use of least squares regression. To facilitate quick learning, the Third Edition stresses the use of graphical methods in an effort to find appropriate models and to better understand them. In that spirit, most analyses and homework problems use graphs for the discovery of structure as well as for the summarization of results.
The Third Edition incorporates new material reflecting the latest advances, including:
Readers will also find helpful pedagogical tools and learning aids, including:
With its focus on graphical methods and analysis, coupled with many practical examples and exercises, this is an excellent textbook for upper-level undergraduates and graduate students, who will quickly learn how to use linear regression analysis techniques to solve and gain insight into real-life problems.
"Sinopsis" puede pertenecer a otra edición de este libro.
Applied Linear Regression, Second Edition is a comprehensive guide to the methods of applied linear regression. Focusing on model building, assessing fit and reliability, and drawing conclusions, it develops estimation, confidence, and testing procedures mostly using least squares. Throughout, the importance of assumptions and their relevance in specific problems is stressed. Updated to reflect the enormous progress in the area of linear regression since the First Edition in 1980, the Second Edition cites more than 60 references, and includes several new problems, figures, and a totally new chapter that introduces students to nonlinear, logistic, and generalized linear regression models. Containing more than 20 worked examples, real data is used to illustrate variable selection, new predictor construction and dummy variables, model validation and other topics. Applied Linear Regression, Second Edition provides the most in-depth coverage available on transforming variables, finding problems with assumptions, and identifying influential cases. It discusses the special problems of inference and prediction from regression models. And throughout, graphical methods are generously discussed and illustrated. Additional topics include:
SANFORD WEISBERG, PhD, is Professor of Statistics and Director of the Statistical Consulting Service at the University of Minnesota. He has authored or coauthored three popular texts for John Wiley & Sons, Inc. and is a Fellow of the American Statistical Association.
"Sobre este título" puede pertenecer a otra edición de este libro.
Descripción Wiley, 2005. Hardcover. Estado de conservación: New. New Book. Nº de ref. de la librería 6890-000017May336065
Descripción Wiley, 2005. Hardcover. Estado de conservación: New. Never used!. Nº de ref. de la librería P110471663794
Descripción Wiley, 2005. Hardcover. Estado de conservación: New. Brand New!. Nº de ref. de la librería VIB0471663794
Descripción Wiley, 2005. Hardcover. Estado de conservación: New. book. Nº de ref. de la librería M0471663794