Stat 704, Fall 2014

STAT 704: Data Analysis I, Fall 2014

Instructor: Tim Hanson. E-mail: hansont@stat.sc.edu.
Office Hours: Tuesday/Thursday 10-11am, and by appointment.
Office: 219C LeConte College, (803) 777-3859.
Class Meeting Time: Tuesday/Thursday 11:40am-12:55pm in LeConte College 201A.
Textbook: Applied Linear Statistical Models (5th edition) by Kutner, Nachtsheim, Neter, and Li.

Lecture schedule and notes

  • Thur., Aug. 21: Random variables, expectation, densities for common distributions. Course notes. Textbook data sets are available here.
  • Tues., Aug. 26: Normal data inferences, two sample problem, quantile-quantile plots. Course notes. R code for Q-Q plot examples.
  • Thur., Aug. 28: Normal data, continued. Homework 1.
  • Tues., Sep. 2: One and two-sample nonparametric tests. Course notes.
  • Thur., Sep. 4: Chapter 1: simple linear regression. Course notes. A Java applet illustrating least squares estimation.
  • Tues., Sep. 9: Chapters 1 and 2. Residuals, normal errors, inferences for slope, the line, and predictions. Course notes. Here's another nice set of notes using KNNL examples.
  • Thur., Sept. 11: ANOVA table, general linear test, correlation. Course notes. Homework 2, due Sept. 18. SAS code for 2.26(c).
  • Tues., Sept. 16: Chapter 5. Correlation, matrices, two-sample problem and simple linear regression using matrices. Course notes.
  • Thur., Sept. 18: Multivariate normal distribution. Course notes. Homework 3, due Thursday Sept. 25.
  • Tues., Sept. 23: Chapter 6. Multiple regression in matrix terms. Course notes.
  • Thur., Sept. 25: Chapter 6. Checking assumptions, diagnostics. Course notes. Some online examples of diagnostics in SAS.
  • Tues., Sept. 30: Chapters 3 and 6. Transformations. Course notes.
  • Thur., Oct. 2: Chapter 7: Extra sums of squares, multicollinearity. Course notes. Homework 4, due October 14. Handout on details behind VIFs.
  • Tues., Oct. 7. Chapter 7 continued. Surgical unit example in SAS.
  • Thur., Oct. 9. Review for Exam I. Course notes.
  • Tues., Oct. 14. Exam I.
  • Thur., Oct 16: Chapter 8. Polynomial and categorical predictors, interactions. Course notes.
  • Tues., Oct. 21: Chapter 9. Model selection and validation. Course notes. Homework 5, due Nov 6.
  • Thur., Oct. 23. FALL BREAK! No class.
  • Tues., Oct. 28. Chapter 9.
  • Thur., Oct. 30. Chapter 9.
  • Tues., Nov. 4. ELECTION DAY. No class.
  • Thur., Nov. 6. Chapter 10. Diagnostics. Course notes.
  • Tues., Nov. 11. Chapter 10.
  • Thur., Nov. 13. Chapter 10. Examples: SAS code for arterial pressure data and other examples. Homework 6 Due November 20.
  • Tues., Nov. 18. Chapter 11: Weighted least squares and ridge regression. Notes.
  • Thur., Nov. 20. Chapter 11: Robust and quantile regression. Notes. Homework 7, due Tuesday Dec. 2.
  • Tues., Nov. 25. Generalized additive models. Notes.
  • Thur., Nov. 27. THANKSGIVING. No class.
  • Tues., Dec. 2. Review for Exam II.
  • Thur., Dec. 4. Exam II. Glippers data in text and CSV formats. Final exam.

    • Review Material

    You should be acquainted with elementary probability, including discrete and continuous random variables, sampling distributions, point and interval estimation, and hypothesis testing. If you need to review, there are many sets of notes online, for example these excellent notes from Dr. Tebbs.