Resources suggestion about linear model I was wondering if you could tell me about some self-learning resources for linear model theories. My professor has been using "A First Course in Linear Model Theory, Ravishanker and Dey. Publisher: CRC." I found this kinda difficult. My major is mathematics. Thank you so much for your time!
 A: Reading the whole book on just linear models may be an overkill. This will be especially inefficient if the book is all about "traditional" thinking and does not present a detailed overview of regularization. In many situations, regularization allows one to improve estimation methods for linear models, generating techniques like lasso, ridge regression, elastic nets, least angle regression and principal components regression (I will stress: all of those are methods for linear models.). I have discovered that all major facts about linear models are covered by
chapter 3 of Hastie, T., Tibshirani, R., & Friedman, J. H. (2008). The elements of statistical learning: Data mining, inference, and prediction. New York: Springer.
and
chapters 2-5 of Greene, W. H. (2012). Econometric Analysis (7th ed). Upper Saddle River, NJ: Prentice Hall. 
A: I would recommend you 
Pedhazur, E. J. (1997). Multiple regression in behavioural research Fort Worth. TX: Harcourt Brace College Publishers.
Of all books on regression that I have had a chance to read, the one by Pedhazur is the easiest to understand. He covers the basics of regression, explaining each concept by using easy to follow examples. Also, he provides a great account of how to test regression assumptions. The bit that I found the most satisfying was a complete step by step example of matrix calculations in parameter estimation. In my humble view, this book is gold for those who want to understand regression deeply
