MATH 410B - Advanced Statistical Methods II

Description:
Further topics in applied statistics, including time series analysis, principal components analysis, cluster analysis, and nonparametric statistics. Emphasis on applied model evaluation and diagnostics. Course will be offered every year (Winter).

Prerequisites:
Prerequisite: MATH 410A with a grade of C or higher.

Credits: (4)

Learner Outcomes:
Upon successful completion of this course, the student will be able to:

Choose an appropriate regression-based time series model for a data set.
Evaluate the fit of a time series model and interpret predicted values and prediction and confidence intervals.
Evaluate the results of a principal components analysis.
Choose an appropriate decision tree model.
Choose between various methods of cluster analysis, including K-means and hierarchical clustering, and justify a choice for the number of clusters.
Conduct a major statistical project, choosing appropriate statistical tools and evaluating the models appropriately.
Communicate statistical results clearly orally and in writing.

Learner Outcomes Approval Date:
3/1/18