About

Statistics 674: Time Series (2 units)

Course Description:

Analysis of correlated data in time, trends, seasonal patterns, periodicity, autocorrelation, spectral analysis, filtering, time domain versus spectral domain. Decomposition, auto-regression, ARIMA, state-space models, forecasting. Applications using to collect data in economics, engineering, seismology. Report writing. Use of statistical software.

Prerequisites:

STAT 632

Possible Instructional Methods:

Entirely On-ground.

Grading:

A-F or CR/NC (student choice).

Student Learning Outcomes

Upon successful completion of this course students will be able to:

  1. Graphically display and numerically describe time-dependent data.
  2. Derive and understand the theory of point and interval estimation for forecasting.
  3. Formulate and model practical problems for solutions using these statistical methodologies.
  4. Produce relevant computer output using standard statistical software and interpret results appropriately.
  5. Communicate statistical concepts and analytical results clearly and appropriately to others.