Class Notes 1 Introduction, Simple Linear Regression
Class Notes 2 Theory and Inference for Simple Linear Regression
Class Notes 3 Inference for a Mean Response, Prediction Intervals
Class Notes 4 Sums of Squares and the Regression Model F Test
Class Notes 5 General Linear F Test, R Squared, Checking Assumptions
Class Notes 6 F Test for Lack of Fit
Class Notes 7 Regression Through the Origin
Class Notes 8 Matrix Approach to Regression
Class Notes 9 Random Vectors and Matrices
Class Notes 10 Intro to Multiple Regression, Matrix Approach to Multiple Regression
Class Notes 11 Estimation, Sums of Squares, Regression Model F Test, R Squared for Multiple Regression
Class Notes 12 Theory and Inference for Multiple Regression
Class Notes 13 Extra Sums of Squares
Class Notes 14 Partial F Tests, Partial R-Squared
Class Notes 15 Multicollinearity, General Linear Models, Polynomial Regression
Class Notes 16 Models with Interactions
Class Notes 17 Models with Quantitative and Qualitative Predictors
Class Notes 18 Models with Quantitative and Qualitative Predictors (Cont’d)
Class Notes 19 Model Selection
Class Notes 20 Automated Model Selection Procedures
Class Notes 21 Model Validation, Model Diagnostics
Class Notes 22 Autocorrelation and Time Series Analysis
Class Notes 23 Logistic Regression
Class Notes 24 Poisson Regression
Class Notes 25 Nonparametric Regression and Scatterplot Smoothers
Class Notes 26 Nonparametric Regression and Scatterplot Smoothers (Cont’d)