Statistics 451 - Applied Time Series
Spring 2014

Instructor: William Q. Meeker, 294-5336
Instructor email:
Office Hours: MWF 2:10-3:00 p.m. in 2019 Snedecor Hall (or by appointment---send email)
Lecture: MWF 12:10-1:00, Sweeney 1126
Assignments: Due weekly on Fridays, unless announced otherwise.
Examinations: Two one-hour exams plus a two-hour final examination.

Statistics 451 homepage:
Text: None required; see suggested reading below
Class Notes: Available from the course homepage.

Tentative Schedule

  1. Introduction to time series and time series models. (Handout 1 and Chapters 1 and 2, 2 days)
  2. Review of multiple regression and descriptive methods, and further introduction to time series analysis. (Handout 1A; 6 days) Graphical techniques, transformations, analysis of residuals, autocorrelation.
  3. Fundamental concepts of time series modleing. (Handout 2, Chapters 1 and 3; 10 days) Stochastic processes, process and sample autocorrelation function, partial autocorrelation function.
  4. Stationary time series models. (Handouts 3 and 4, Chapter 3; 6 days) ARIMA models, model identification. Nonstationary time series. (Handout 5, Chapter 4; 3 days) Differencing, transformation, identification.
  5. Estimation in time series. (Handout 6; 2 days) Nonlinear least squares, potential problems, diagnostic checking and residual analysis.
  6. Forecasting and prediction intervals. (Handout 7, Chapters 4 and 5; 4 days)
  7. Seasonal time series models. (Handout 8, Chapter 5; 3 days) SARIMA models, identification, estimation, forecasting.
  8. Transfer function and intervention models. (Handouts 9 and 10, Chapters 8; 11 days)
  9. Vector (multivariate) time series. (Chapter 9, notes; 3 days)
Recommended Reading:
Time Series Analysis and Forecasting by Example by Soren Bisgaard and Murat Kulahci, John Wiley and Sons.
Time Series Analysis - Univariate and Multivariate Methods (Second Edition) by William W.S.Wei

Supplementary Reading:
Time Series Analysis: Forecasting and Control by G.E.P. Box and G.M. Jenkins
Practical Experiences with Modeling and Forecasting Time Series by G.M. Jenkins

Students with disabilities
Please address any special needs or special accommodations with me at the beginning of the semester or as soon as you become aware of your needs. Those seeking accommodations based on disabilities should obtain a Student Academic Accommodation Request (SAAR) form from the Disability Resources (DR) office (515-294-6624). DR is located on the main floor of the Student Services Building, Room 1076.

Click here to go to W.Q. Meeker's homepage.