CSI 678 / STAT 658: Time Series Analysis and Forecasting

James Gentle

Time series analysis is used for diverse applications in economics, the social sciences, the physical and environmental sciences, medicine, and signal processing. This course presents the fundamental principles of time series analysis including mathematical modeling of time series data and methods for statistical inference. Models in both the time domain and the frequency domain will be developed and explored.

Course Objectives:
At the end of this course the student should be familiar with the basic concepts of time series analysis and forecasting. The student should be able to use standard computer software to analyze time series to perform simple forecasts. The student should also be prepared to take more advanced courses in time series.



STAT 544 or ECE 528 or equivalent multivariable calculus-based graduate course in Applied Probability or Random Processes.


  • homework assignments (30)
  • midterm exam (30)
  • final exam (40)

    Each homework will be graded based on 100 points, and 5 points will be deducted for each day that the homework is late.


    The main analysis software used in the course will be R. No prior experience with R is assumed.
    Information about R, including links for downloading, can be obtained at http://www.r-project.org/