GLM (SAS & R)

[1] The Simple Linear Regression (SLR) 
   1.1 Intro to SLR model: Equation and Assumptions
   1.2 Estimation for the SLR: the Least Squares Method
   1.3 The Least Squares Estimators are Unbiased
  
[2] The General Linear Model (GLM)
   2.1 Intro to GLM: Hypothesis and Assumptions, One-Way ANOVA 
   2.2 Two-Way ANOVA : Hypothesis, Model and Table
   2.3 Case Study: The Pygmalion Effect, in SAS Two-Way ANOVA

[3] Comparing Two Groups  
   3.1 Intro to two sample T-test & Case Study: the Spock Conspiracy Trial 
   3.2 Case Study: The Spock Conspiracy Trial, t-test in R
   3.3 Case Study: The Spock Conspiracy Trial, SLR in R
   3.4 Case Study: The Spock Conspiracy Trial, in SAS - by using t-test 
   3.5 Case Study: The Spock Conspiracy Trial, in SAS - by using proc glm    

[4] Comparing More Than Three Groups
   4.1 Intro to Multiple Comparisons - The Bonferroni Method  
   4.2 Case Study : The Spock Conspiracy Trial, in SAS - by using proc glm \w the Bonferroni.

[5] The Generalized Linear Model
   5.1 Intro to the Generalized Linear Model - Link Functions
   5.2 Intro to Binary Logistic Regression - Assumptions, Model, Wald & Likelihood Test
   5.3 Case Study : The Donner Party Example, in SAS - Binary Logistic Regression
   5.4 Intro to Binomial Logistic Regression - Model, Deviance & Global LR Test
   5.5 Case Study : The Krunnit Island, in SAS - Binomial Logistic Regression
   5.6 Intro to Poisson Regression Model - Model, Model Assessment 
   5.7 Case Study : Mating Success of Elephants, in SAS - Poisson Regression
   5.8 Intro to Contingency Table (IxJ) - Hypothesis, Assumption, Chi-Squared test.  
   5.9 Case Study : Framingham Heart Study, in SAS - 2x2 table (Chi-squared test)