Inference Methods in Biostatistics
Subject MAST90100 (2016)
Note: This is an archived Handbook entry from 2016.
Credit Points: | 12.5 | ||||||||||||
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Level: | 9 (Graduate/Postgraduate) | ||||||||||||
Dates & Locations: | This subject has the following teaching availabilities in 2016: April, Parkville - Taught on campus.
Timetable can be viewed here. For information about these dates, click here. | ||||||||||||
Time Commitment: | Contact Hours: 24 hours Total Time Commitment: 170 hours | ||||||||||||
Prerequisites: | The following subject may be taken concurrently 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
Prof John CarlinContact
Melbourne School of Population and Global Health
OR
Currently enrolled students:
- General information: https://ask.unimelb.edu.au
- Email: enquiries-STEM@unimelb.edu.au
Future Students:
- Further Information: http://mspgh.unimelb.edu.au/
- Email: Online Form
Subject Overview: |
This subject provides the foundation theory and methods needed for biostatisticians to apply and critically interpret statistical inference, the science of drawing conclusions from data that are subject to variability. Major topics include review of the key concepts of estimation including sampling variability and construction of confidence intervals; null hypothesis testing; methods of inference based on likelihood theory (Fisher and observed information, likelihood ratio, Wald and score tests); and an introduction to the Bayesian approach to inference. The approach will emphasise a critical understand¬ing of the role of statistical inference in health research. |
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Learning Outcomes: |
To provide a strong mathematical and conceptual foundation in the methods of statistical inference, with an emphasis on practical aspects of the interpretation and communication of statistically based conclusions in health research. |
Assessment: |
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Prescribed Texts: |
Marschner IC. Inference Principles for Biostatisticians. CRC Press, 2015. |
Breadth Options: | This subject is not available as a breadth subject. |
Fees Information: | Subject EFTSL, Level, Discipline & Census Date |
Generic Skills: |
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Related Course(s): |
Graduate Diploma in Biostatistics Master of Biostatistics |
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