Applied Linear Regression

by Sanford Weisberg

Master linear regression techniques with a new edition of a classic text Reviews of the Second "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, Readers will also find helpful pedagogical tools and learning aids, 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.

Genres: Mathematics, Reference, Textbooks

336 pages, Hardcover

First published January 1, 1980

Reviews

[Shelby Gonzalez · Rating 3 out of 5]

Read for my stats class on linear regression. Definitely hard to stay awake while reading sometimes

[RA · Rating 4 out of 5]

I read the fourth edition and was happy to learn a number of things that were new to me. Not everything was easy to understand or complete, but I was not disappointed, it is a book worth reading, although as for most other statistics books, one cannot expect to cover everything.

[Shika · Rating 3 out of 5]

Assumes you have linear algebra/strong mathematical background. If you're a biologistic looking to starting in Biostatistics, would recommend looking elsewhere. If you're a statistician looking for applied linear regression basics, then this would be better suited for you.

[Goo · Rating 2 out of 5]

I read some of this as a secondary text when first learning the theory of linear normal models. My primary text lacked certain aspects of actually applying linear models which this text covered in a simple fashion. However, the text is not suited as an introduction to the mathematical theory behind linear models.

[Patrick · Rating 2 out of 5]

I read this as a graduate student in statistics, there are many better books.