Linear Models
Subject POPH90120 (2015)
Note: This is an archived Handbook entry from 2015.
Credit Points: | 12.5 | ||||||||||||||||||||||||
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Level: | 9 (Graduate/Postgraduate) | ||||||||||||||||||||||||
Dates & Locations: | This subject has the following teaching availabilities in 2015: Semester 1, Parkville - Taught online/distance.
Semester 2, Parkville - Taught online/distance.
Timetable can be viewed here. For information about these dates, click here. | ||||||||||||||||||||||||
Time Commitment: | Contact Hours: None Total Time Commitment: 170 hours | ||||||||||||||||||||||||
Prerequisites: |
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Subject Study Period Commencement: Credit Points: | ||||||||||||||||||||||||
Corequisites: | None | ||||||||||||||||||||||||
Recommended Background Knowledge: | None | ||||||||||||||||||||||||
Non Allowed Subjects: | None | ||||||||||||||||||||||||
Core Participation Requirements: |
For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Students Experiencing Academic Disadvantage Policy, academic requirements for this subject are articulated in the Subject Description, Subject Objectives, Generic Skills and Assessment Requirements of this entry. |
Coordinator
Assoc Prof Julie SimpsonContact
julieas@unimelb.edu.au (Semester 1)
john.carlin@unimelb.edu.au (Semester 2)
OR
Academic Programs Office
Melbourne School of Population and Global Health
Tel: +61 3 8344 9339
Fax: +61 3 8344 0824
Email: sph-gradinfo@unimelb.edu.au
OR
Biostatistics Collaboration of Australia
Email: bca@ctc.usyd.edu.au
Website: www.bca.edu.au
Subject Overview: |
The method of least squares; regression models and related statistical inference; flexible nonparametric regression; analysis of covariance to adjust for confounding; multiple regression with matrix algebra; model construction and interpretation (use of dummy variables, parameterisation, interaction and transformations); model checking and diagnostics; regression to the mean; handling of baseline values; the analysis of variance; variance components and random effects. |
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Learning Outcomes: |
To enable students to apply methods based on linear models to biostatistical data analysis, with proper attention to underlying assumptions and a major emphasis on the practical interpretation and communication of results. |
Assessment: |
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Prescribed Texts: |
Resources Provided to Students: Printed course notes and assignments by mail, email, and online interaction. Special Computer Requirements: Stata statistical software |
Recommended Texts: |
Kutner MH, Nachtsheim CJ, Neter J, Li W. Applied Linear Statistical Models. 5th edition. McGraw-Hill/Irwin 2005. ISBN 978-0-07-310874-2 |
Breadth Options: | This subject is not available as a breadth subject. |
Fees Information: | Subject EFTSL, Level, Discipline & Census Date |
Generic Skills: |
Independent problem solving, facility with abstract reasoning, clarity of written expression, sound communication of technical concepts |
Links to further information: | http://www.sph.unimelb.edu.au |
Notes: |
This subject is not available in the Master of Public Health.
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Related Course(s): |
Master of Biostatistics Postgraduate Certificate in Biostatistics Postgraduate Diploma in Biostatistics |
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