Linear Regression Analysis

by George A.F. Seber, Alan J. Lee

Concise, mathematically clear, and comprehensive treatment of the subject.
* Expanded coverage of diagnostics and methods of model fitting.
* Requires no specialized knowledge beyond a good grasp of matrix algebra and some acquaintance with straight-line regression and simple analysis of variance models.
* More than 200 problems throughout the book plus outline solutions for the exercises.
* This revision has been extensively class-tested.

592 pages, Hardcover

First published January 1, 1977

Reviews

[Goo · Rating 3 out of 5]

I used this as a secondary reference when first learning the theory of linear normal models. This book is in the middle ground when it comes to the level of abstraction. Most formulas are written using matrix products instead of the more abstract "coordinate-free" approach where everything is written as projections, norms and inner products. Both approaches have their advantages - this book gives better hand-on feeling for the formulas, whereas the coordinate-free approach helps with building intuition. Highly recommended.