STAT 474 - Introduction to Time Series and Forecasting

Units: 3
Analysis of correlated data in time, trends, seasonal patterns, periodicity, autocorrelation, spectral analysis, filtering, time domain versus spectral domain. Decomposition, auto-regression, ARIMA, and forecasting. Applications to data in economics, engineering, seismology. Report writing. Use of computer software.

Prerequisites: One of: STAT 100, STAT 110, STAT 303, STAT 316, STAT 330.
Possible Instructional Methods: Entirely On-ground.
Grading: A-F or CR/NC (student choice).
Course Typically Offered: Variable Intermittently

Student Learning Outcomes - Upon successful completion of this course students will be able to:

apply basic computational skills in descriptive statistics and data visualization, hypothesis testing, confidence intervals, modeling and error analysis, including the use of large data sets;
analyze data using appropriate software, including cloud-based software, and to interpret results covering descriptive statistics and data visualization, hypothesis testing, confidence intervals, modeling and error analysis, including the use of large data sets;
communicate to non-statisticians results involving descriptive statistics and data visualization, hypothesis testing, confidence intervals, modeling and error analysis using reproducible research best practices.