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Topics include review of statistics; F and X 2 distributions; review of simple linear regression model; multiple linear regression model; hypothesis testing, forecasting, diagnostics with regression models (including heteroskedasticity, serial correlation and model specification). Examples drawn from economics, finance, accounting, marketing and management will be illustrated using EVIEWs.
Intended learning outcomes
- Apply the least-squares method of estimation to the context of the simple linear regression model.
- Apply the principles of the least-squares method of estimation and inference to the multiple linear regression model.
- Apply EViews to estimate, test hypotheses and forecast in the context of the linear regression model.
- Explain various problems that arise from applying the linear regression model to data, including multicollinearity, specification errors, heteroskedasticity, nonstationarity and autocorrelation.
High level of development: written communication; collaborative learning; problem solving; team work; statistical reasoning; application of theory to practice; interpretation and analysis; critical thinking; synthesis of data and other information; use of computer software.
Moderate level of development: oral communication; evaluation of data and other information; accessing data and other information from a range of sources; receptiveness to alternative ideas.
Last updated: 24 March 2020