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