Introduction to Statistical Computing

Statistics 406

Course notes:
Course overview
An overview of R programming
Expected values and the sample mean
ev-1.R, ev-2.R, ev-3.R, ev-4.R, ev-5.R, ev-6.R, ev-7.R, ev-8.R, ev-9.R, ev-10.R, ev-11.R
Estimating the expected value with non-iid data
nv-1.R, nv-2.R, nv-3.R, nv-4.R, nv-5.R
Confidence intervals
ci-1.R, ci-2.R, ci-3.R, ci-4.R, ci-5.R, ci-6.R, ci-7.R
Estimation
es-1.R, es-2.R, es-3.R, es-4.R, es-5.R
Likelihoods
lk-1.R, lk-2.R
10/23 practice with MLE's
Hypothesis tests
ht-1.R, ht-2.R, ht-3.R, ht-4.R, ht-5.R, ht-6.R
Binary data
ct-1.R, ct-2.R, ct-3.R
Correlation and regression
cr-1.R

Code:
uniform_properties.R
rare_events_coins.R
birthday_matches.R
cross_street.R
percolation.R
urn_1.R
cluster_bootstrap.R
pilot_sample.R
cluster_shrinkage.R
overview.R
NHANES example program

Problem sets:
Problem set 1 (solutions)
Problem set 2 (solutions)
Problem set 3 (solutions)
Problem set 4 (solutions)
Problem set 5 (solutions)
Problem set 6 (solutions)
Problem set 7
Problem set 8
Problem set 9
Problem set 10

Exam information:
The exam will take place on November 15th during class.
2007 exam with solutions
2005 exam
Practice problems for the exam, with solutions
2006 exam, with solutions

R:
Download R here (choose the precompiled binary for your system).
R for older Macs

Data:
NHANES
NHANES practice exercises