Statistics Modeling

The course introduces the concepts of simple linear regression and multiple regression analysis through discussion of the assumptions underlying linear regression models, diagnostic tests, and correction methods for heteroscedasticity, multicollinearity and serial correlations. The course also presents deterministic and stochastic time series models and includes the basic smoothing and extrapolation techniques, model specification, parameter estimation and forecasting for the different time series models. Prerequisite: STA 315.