STAT3030
Generalized Linear Models
10 Units
Available in 2013
| Callaghan Campus | Semester 1 |
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Previously offered in 2012, 2011, 2010, 2009, 2008, 2007, 2006, 2005, 2004
How do we model data of very different types in a consistent way? This course explores generalized linear models and illustrates how methods for analysing continuous and categorical data fit into this framework.
| Objectives | On successful completion of this course, students will be able: 1.To help students understand and use the principles of statistical modelling; 2.To provide a unified conceptual and theoretical framework for many of the most commonly used statistical methods including multiple linear regression, analysis of variance and logistic regression; 3.To develop skill in statistical computing. |
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| Content | Topics include: . Linear models . Model fitting as an approach to statistical analysis . Exponential family of distributions . Maximum likelihood estimation . Inference methods based on model fitting . Generalised Linear Models . Models for continuous data (regression analysis of variance) . Models for categorical data (logistic regression for nominal and ordinal data, Poisson regression and log-linear models) . Generalised Additive models |
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| Replacing Course(s) | n/a | ||||
| Transition | n/a | ||||
| Industrial Experience | 0 | ||||
| Assumed Knowledge | STAT2010 Fundamentals of Statistics STAT2000 Applied statistics and Research Methods |
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| Modes of Delivery | Internal Mode | ||||
| Teaching Methods | Lecture
Computer Lab |
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| Assessment Items |
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| Contact Hours | Lecture: for 2 hour(s) per Week for Full Term Computer Lab: for 2 hour(s) per Week for Full Term |
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| Timetables | 2013 Course Timetables for STAT3030 |