MATH 311: Regression and Time Series Models

(1 Unit)
Covers two topics in detail: multiple linear regression analysis and time series analysis. Inherent to both topics: parsimonious linear models, parameter estimation, diagnostic checking, and forecasting. Uses the matrix approach for multiple linear regression, and the Box-Jenkins methodology for constructing autoregressive-integrated moving average (ARIMA) models for time series analysis. Employs the statistical package MINITAB for analyzing all real-world data sets. Anderson.