Lecture notes

• Latin square and split plot designs. Last updated: 5/4. Data sets: millet and oats
• Mean Squares approach for RCBD with and without subsampling. Data sets: seed emergence.
• Mean Squares approach for CRD with and without subsampling. Data sets: irrigation and loblolly stomata density.
• Mutlilevel models: introduction, and likelihood ratio tests. Data sets: corn and floweringTime.
• Causal inference and randomization. Data set: fev.
• Simulations for inference. Data set: seaweed.
• Poisson regression (last updated: 2/23). Data sets: acf and moths.
• Model selection and logistic regression. The logistic regression section was exanded (2/10). Data sets: anesthetic.txt. Baby food
• Multiple linear regression: linear and log transformations, significance with f-test and t-tests, correlated predictors. Pesticide toxicity data set: toxic.txt.
• Multiple linear regression. Birds and bats case study: bats.txt.
• Introduction and quick review of simple linear regression.