Show Introduction to Time SeriesPeople
Lectures: Cory 241. Tuesday/Thursday 12:30 - 2:00.Classroom and Computer Lab Section: Evans 344. Friday 9-11.Course Outline:An introduction to time series analysis in the time domain and frequency domain. Topics will include: Stationarity, autocorrelation functions, autoregressive moving average models, partial autocorrelation functions, forecasting, seasonal ARIMA models, power spectra, discrete Fourier transform, parametric spectral estimation, nonparametric spectral estimation.Text:Time Series Analysis and its Applications. With R Examples., by Robert H. Shumway and David S. Stoffer. Springer. 2nd Edition. 2006. web site.Prerequisites:101, 134 or consent of instructor.Assessment:Lab/Homework Assignments (25%): posted every one to two weeks, and due on Fridays at 9 (at the start of the section). The grade will be the average of all homework grades except the worst.Midterm Exams (30%): scheduled for October 7 and November 9, at the usual lecture time and place. Midterm 1: pdf Solutions: pdf. Midterm 2: pdf Solutions: pdf. Project (10%). Final Exam (35%): scheduled for Friday 12/17/10. Lab/Homework Assignments:
Lectures:Chapter/section references are to Shumway and Stoffer.
Announcements:
Collaboration:You are encouraged to work in small groups on homework problems; it's an excellent way to learn. However, you must write up the solutions on your own, and you must never read or copy the solutions of other students. Similarly, you may use books or online resources to help solve homework problems, but you must credit all such sources in your writeup and you must never copy material verbatim.Academic Dishonesty:Any student found to be cheating risks automatically failing the class and being referred to the Office of Student Conduct. In particular, copying solutions, in whole or in part, from other students in the class or any other source without acknowledgment constitutes cheating. |