This course coveres multiple linear regression models and examples and graphical methods for regression analysis. It also covers multi-variate normal distribution, quadratic forms (distributions and independence), Gauss-Markov theorem, hypothesis testing, model selection, analysis of residuals, influence diagnostics and analysis of variance.
Where content is in common with MATH2831, this course aims to give students a deeper level of understanding.
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