MATHS 428: Regression and Time Series Models (3)

Syllabus

1.  Prerequisite: MATHS 321 or equivalent.

2.  Course Description: Addresses regression topics that include simple and multiple linear regression, polynomial regression, regression diagnostics, and forecasting. Introduces time series topics that include exponential smoothing, auto-regressive, integrated, moving average (ARIMA) models, and forecasting.

3.  Course Objectives: The course serves as an introduction to regression models. It also serves as a brief introduction to time series models. A primary focus of both of these main topics is that of forecasting. Students will identify and demonstrate appropriate understanding of the key steps in modeling with regression and time series, including model specification, estimation of parameters, diagnostics, and forecasting. Students will use statistical software packages for analysis and forecasting.

4.  Course Rationale: This course is intended to provide an introduction to the topics of regression and time series, two modeling techniques that are essential parts of the statistician’s expertise. At the same time, the course addresses a variety of advanced topics that are recommended for study by the Society of Actuaries.

5.  Course Content:

Regression Simple linear regression Correlation Multiple regression Partial correlation Hypothesis testing Forecasting

Time Series Identification of ARIMA models Estimation of parameters Diagnostic checking Forecasting

6.  Course Format: The class will be taught through a lecture/discussion format. Students will be expected to participate in class regularly, to study the material in the textbook, and to complete a variety of assignments using statistical software.

7.  Evaluation of Student Performance: Course grades are determined primarily by student performance on tests, quizzes, and projects, as well as possibly homework and class participation. The evaluation and weight of these various components are at the discretion of the individual instructor.

8.  Evaluation of the Course: The instruction of the course is evaluated by departmental student evaluations and peer evaluations. The course is reviewed and revised periodically by the Department Undergraduate Programs Committee.

[VDM 10/2005]