Applied Linear Statistical Models: Regression, Analysis of Variance, and Experimental Designs

Experimental design analyzing with linear models has been on the notation for decades. The book, although somewhat antique, is still an envaluable reference.

I have used this book when it was in its first edition and only by Neter and Wasserman. An absolute must for those who use linear models (regression and ANOVA) and want the most exhaustive book out there. This book is one of the rare texts that is also extremely well written. You can not go wrong reading it and studying it on your own. If you can take only one statistics book with you, this is the one. I use the 4th edition so much, I wore my first one out and am now on the second.

This book seems very difficult and long to read at first, but as soon as I got into the habit of using this book, this is really a great book to have. The terminologies are very easy to understand and yet not redundant, and it has some great reference areas in the sections that you could look up for information when you need to work on an exercise or a project. The exercises in the back of each section are ample enough so that you can have a firm grasp of the material after working on those exercise. This book is useful and is a must have for any math/stat student!Enjoy...

The linear model lies at the heart of a wide variety of familiar statistical methods, including regression, anova, and ancova. Anyone with a professional interest in statistics must get to know it well. This book is a clear, well organized, and practical presentation of the linear model. It is not pie-in-the-sky or esoteric. It leads the reader carefully through the real world problems that are encountered in applying the model. The book can be read on several levels. It provides practical instructions for applying the model to various situations, but also quite thoughly expounds on the mathematical theory behind the model. The theory and practice are separate but parallel, so you can read as much or as little of the theory as you like, or as much or as little of the practice. This book belongs on the reference shelf of anyone who uses statistics. In a world where technical publications are priced through the sky, it is a relative bargain (1400 pages).

I definitely recommend this book to anyone who wishes to understand how to implement the linear model. This book shows the theory and then gives comprehensive examples explaining when and how to apply the theory. The book made few assumptions about readers having a certain level of specialized knowledge, such as familiarity with matrix math. The math presented in the book is thoroughly explained from the ground up using concrete examples, well over 1000 pages of text. I wish all advanced mathematical, engineering and science books were written in a similar fashion, presenting abstract theories along with in-depth concrete examples.