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Linear Models in Statistics (6 points)


Leader: Dr Malcolm Clark

Clayton First semester 2003 (Day)

Synopsis: The simple linear regression model. Least squares fitting of multiple regression; significance tests and confidence intervals for regression parameters; residual analysis for adequacy of model; weighted least squares; correlated errors; one-way ANOVA; randomised block; two-way cross classification; 2n factorial experiments; analysis of covariance, confounding and partial confounding; contrasts. It will be assumed that students can use the package Minitab.

Assessment: Examination (3 hours): 80% + Assignments and tests: 20%

Contact Hours: Three 1-hour lectures and an average of one 1-hour support class per week

Prerequisites: STA2022 or equivalent

Prohibitions: MAT3211 or MAT3221

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