MATH 414 - Time Series Analysis

Description:
Model building, parameter estimation, diagnostic checking of time series data; ARIMA models and forecasting. Analysis of seasonal models.

Prerequisites:
Prerequisites: MATH 410A and either MATH 411A or MATH 314, with grades of C or higher.

Credits: (3)

Learner Outcomes, Activities and Assessments

Learner Outcome	Activity (optional)	Assessment
Estimate ARMA and ARIMA models for time series data.	Students will complete statistical lab assignments which require them to estimate ARMA and ARIMA models.	Written lab reports, exams, and a final project.
Evaluate the fit of time series models, and choose appropriate models for a given data set.	Students will complete statistical lab assignments which require them to choose appropriate models and evaluate the fit of their chosen models.	Written lab reports, exams, and a final project.
Assess time series data for trends and seasonality, and estimate models including these terms.	Students will complete statistical lab assignments which require them to use diagnostic checks for trends and seasonality, and fit models including trends and seasonality.	Written lab reports, exams, and a final project.
Evaluate properties of a time series model given in mathematical form, including checking stationarity and computing the autocorrelation function of a given model.	Students will complete homework problems that require them to check properties of a given model, including stationarity and computing the autocorrelation function.	Graded homework problems and exams.
Communicate statistical information professionally in writing.	Students will write lab reports for their statistical lab assignments and complete a final project where the tools from the course are applied to a time series data set of their choosing.	Written lab reports and the final project will be assessed using a rubric that includes the clarity and quality of the writing.