Statistics 600

Applied statistics and data analysis I

Notes:

Introduction to R
Least squares
Decomposing variance
Misspecification and confounding
Diagnostics, transformations
Model selection
Prediction
Fixed effects and clustered data

Problem sets:

Problem set 1 (solutions)
Problem set 2 (solutions)
Problem set 3 (solutions)
Problem set 4

Code examples:

1.R Sampling properties of regression coefficient estimates
2.R Coverage probabilities for regression coefficient interval estimates
3.R Basic NHANES analysis
4.R Large sample behavior of the test statistic, R^2, and partial R^2
5.R Confidence and prediction bands for polynomial regression
6.R Cook's distances
7.R Box-Cox transformations
8.R Ridge regression solution paths
9.R Ridge regression MSE
10.R Fixed/random effects, GLS, and clustered data
10.R Fixed/random effects, GLS, and clustered data
11.R Nonparametric regression

Data sets:

NHANES-1.gz

Exam 1, with solutions (#4c corrected on 10/20)