- Review points.
- Factorial and split plot designs. Data sets: alkaloid content, and oats.
- Mean Squares approach for RCBD with and without subsampling, and for the Latin square design. Data sets: seed emergence, millet yield.
- Mean Squares approach and f-test for CRD with and without subsampling. Data set: irrigation.
- Testing random and fixed effects with the likelihood ratio test. Data sets: pygmy marmoset language and flexible learning in bilingual infants.
- Models with random effects: introduction and estimation of coefficients. Last updated: 3/24. Data sets: corn and floweringTime.
- Causal inference and randomization.
- Three-way interactions, overdispersion, and simulations for inference. Data set: lupine seedling survival.
- Logistic regression: the logistic curve,
interpretation of coefficients, chi-square (LRT) test, the problem
of perfect separation.
Updated with graphs on 3/5.

Data sets: anesthesia, runoff, baby food, S.aureus. - Model selection: significance with f-test and t-tests, correlated predictors. Pesticide toxicity data set: toxic.txt. Model selection with different criteria and different search methods.
- Multiple linear regression: re-parametrizations, two-way interactions, linear and log transformations, polynomial regressions. Mussel shell thickness data set: freemanByers.txt. Answers to the 5-question quiz on slide 20.
- Multiple linear regression: interpretation of a linear model. Birds and bats case study: bats.txt.
- Introduction and quick review of simple linear regression. fev data set.

Last modified: Wed May 5 13:41:59 CDT 2010