Regression with Graphics: A Second Course in Applied Statistics...

Features

• Cover Type: Hard Cover with 384 pages
• Published by: Duxbury Press
• Edition: 1st Edition November 14, 1991
• Written in: English
• ISBN 10 Number: 0534159001
• ISBN 13 Number: 978-0534159009
• Book Dimensions: 9.3 x 7.5 x 0.8 inches
• Weighs: 1.6 pounds

Book Description
This text demonstrates how computing power has expanded the role of graphics in analyzing, exploring, and experimenting with raw data. It is primarily intended for students whose research requires more than an introductory statistics course, but who may not have an extensive background in rigorous mathematics. It's also suitable for courses with students of varying mathematical abilities. Hamilton provides students with a practical, realistic, and graphical approach to regression analysis so that they are better prepared to solve real, sometimes messy problems. For students and professors who prefer a heavier mathematical emphasis, the author has included optional sections throughout the text where the formal, mathematical development of the material is explained in greater detail. REGRESSION WITH GRAPHICS is appropriate for use with any (or no) statistical computer package. However, Hamilton used STAT A in the development of the text due to its ease of application and sophisticated graphics capabilities. (STATA is available in a student package from Duxbury including a tutorial by the same author: Hamilton, STATISTICS WITH STAT A, 5.0, 1998; ISBN: 0-534-31874-6.)

About The Author
Ph.D., University of Colorado at Boulder

Reader Reviews
This book covers almost all the topics one would like a practioner to know, but briefly and with emphasis on graphic examination of the data. It is assumed the reader has access to some statistical package. A brief list of topics I was pleased to find in this book: quantile plots (p. 11!), transformations, partial regression leverage plots, dummy variables, a chapter examining assumptions of OLS regression (incl multicollinearity), exploratory band regression, non-linear regression, robust regression, logit regression, and principal componenet analysis. All the simple linear regression stuff is here, with relationship to analysis of variance. People come to me to ask questions about regression, and this book illustrates all the "gotchas" I want to warn them about. I recently went through 6 regression books I have accumulated since the 70's, and I find this book the one I would least like to have disappear off my shelves. Comment | | (Report this)