• Linear Models Introduction Handout
• CPS Introduction R Code
  

• R session from lecture
  

• R code for fitting linear models to CPS data set
• R session from lecture
  

• R session from lecture
  

• R code for confidence/prediction bands with CPS data
• R code for Anorexia example
• Extra reference on multiple comparisons: Boik Lecture Notes (Ch. 19), 2005, Montana State University
  

• R code for SAT data example
• Extra reference on residual diagnostics: Neter, Kutner, Nachtshem and Wasserman, Applied Linear Statistical Models, 4th ed. pp. 95-110.
  

• R code for R-squared simulation

• The midterm exam is closed book and closed notes, but you are allowed to use one 8.5x11" sheet of notes, front and back, handwritten or typed.
• Bring a calculator. (You may not need it, but it's better to have it with you and not use it than need it and not have it.)

Information and Practice Problems for Midterm Exam 1
Solutions to Practice Problems for Midterm Exam 1

• Extra reference on ANOVA (we will cover this after the midterm exam 1), correlation, simple linear regression, multiple linear regression, and F-tests for model comparison: Jones Lecture Notes (Ch. 11-13), 2009, Reed College
• R code for model comparison tests with CPS data set

• Extra reference on Tukey's multiple comparison procedure
• R code for Cuckoo Egg Data ANOVA
  

• R code for two-way ANOVA without replication example
  

• R code for Crack Growth data two-way ANOVA example

• R code for Horse Kick goodness-of-fit example
• R code for Horseshoe Crab goodness-of-fit example
  

• R code for test of homogeneity example
  

• Extra reference on Fisher's Exact Test: C. J. Anderson Lecture Slides, University of Illinois at Urbana-Champaign
  
• R code for lady tasting tea example
  

• R code used in discussion
• Table of data used in example
  

• Extra reference on McNemar's Test: p. 244-247 of Introduction to Categorical Data Analysis, Agresti, 2007.
• R code for Asthma example
  

• Extra reference for DeGroot and Schervich Chapter 10: Chapter 2 of Introduction to Categorical Data Analysis, Agresti, 2007.
• R code for K-S examples
  

• The midterm exam is closed book and closed notes, but you are allowed to use one 8.5x11" sheet of notes, front and back, handwritten or typed.
• Bring a calculator! Calculators on cell phones are not allowed.
  

• Summary handout on nonparametric procedures
  

• R code for Lake Huron example

Additional references on time series:

• Introduction to Time Series and Forecasting by Brockwell and Davis
• If you are on the campus network, you can download chapters of this book for free via link.springer.com.
  
• Time Series Analysis: Forecasting and Control by Box and Jenkins
  

• Additional reference on ARCH and GARCH models
  

• Bootstrap code from lecture
  

• Part 1: Take-home R data analysis due Monday, June 10 at 12pm.
• Part 2: In-class final exam, Monday, June 10, 4-6pm. 

Final exam take-home portion R code with comments. (Note that the R code alone does not constitute an acceptable report!)