Lecture  Slides  Chapter  Extras 

00  Introduction  1  
01  No lecture.  
02  Simple linear regression model; least squares; residuals  2  
03  Introduction to MATLAB  demo.m plot_gpa_fit.m my_regress.m CH01PR19.txt Getting started guide 

04  Normal error regression model; maximum likelihood  
05  Confidence intervals and hypothesis testing in the normal regression model.  
06  Proof of Gauss Markov Theorem  
07  Inference in Normal Regression Model  2.72.10  
08  ANOVA  Cochran’s theorem  
09  Diagnostics and Remedial Measures  3  
10  Remedial Measures and Transformations  4  
11  Joint estimation, Bonferroni joint confidence intervals  5  
12  Linear Algebra Review  Cheat sheets Matrix, Gaussian, Linear Algebra 

13  cont.  
14  cont.  
15  Multivariate Normal Review  
16  cont.  
17  Matrix Linear Regression  5  
18  Multiple linear regression, Testing  6  
19  Quantitative and Qualitative Inputs, Interactions, and Interpretation  8  
20  ANOVA / Extra Sums of Squares  7  
21  Proof of Cochran’s Theorem, extra 