Linear Algebra and Linear Models


Written by R.B. Bapat, published by Springer Publishing.

A Math Book. Not a code book. Sometimes it is useful to read a Math book. Reading a Math book helps you understand what went wrong with your code when all the syntax is correct but the results are a little strange. Knowing the math behind the code helps to figure out what is going on.
Complete with proofs this book on Linear Algebra covers a lot of material.
The proofs are useful in helping understand the language and why its used in Linear Algebra.

Chapter One covers the preliminaries of Linear Algebra. Covers basis and dimension, dim.
Chapter two covers rank, nonsingulars and Frobenuis Inequality.
Chapter three covers eigenvalues for the first time. In addition

Chapter five covers eigenvalues.
Chapter four covers generalized inverses, including Moore-Penrose inverse.

Chapter seven covers General Linear Model, GLM.
Chapter eight tests of linear hypothesis. Cochran’s Theory. A nice table on ANOVA 8.1

Chapter nine Linear Mixed Models.