STAT356 Linear Models
Updated: 14 October 2011| Credit Points | 6 | |||||||||
| Offering |
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| Intensive School(s) | None | |||||||||
| Supervised Exam | There is no UNE Supervised Examination. | |||||||||
| Pre-requisites | STAT261 and PMTH213 | |||||||||
| Co-requisites | None | |||||||||
| Restrictions | None | |||||||||
| Notes | off-campus students must have access to the statistical package R |
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| Combined Units | None | |||||||||
| Coordinator(s) | Robert Murison (rmurison@une.edu.au) | |||||||||
| Unit Description |
A balance between theoretical development and practical application will be maintained. Topics will include: model building, assessing the fit of the model, analysis of residuals; components of a generalised linear model, estimation, analysis of deviance, binary variables, logistic regression. Two lectures and a one-hour laboratory session per week. |
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| Materials | Text information will be published prior to commencement of the teaching period. | |||||||||
| Disclaimer | Unit information may be subject to change prior to commencement of the teaching period. |
| Assessment |
Assessment information will be published prior to commencement of the teaching period.
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| Learning Outcomes (LO) |
Upon completion of this unit, students will be able to:
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| Graduate Attributes (GA) |
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