Principles of Statistical Inference
Subject POPH90017 (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: Semester 1, Parkville - Taught online/distance.
Semester 2, Parkville - Taught online/distance.
This subject is only available to students who are currently enrolled in the Graduate Diploma or Master of Biostatistics and whose enrolment in that course commenced prior to 2016. Timetable can be viewed here. For information about these dates, click here. | ||||||||||||||||||||||||
| Time Commitment: | Contact Hours: None Total Time Commitment: 170 hours | ||||||||||||||||||||||||
| Prerequisites: | The following are pre-requisites for this subject: 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: |
Review of the key concepts of estimation, and construction of Normal-theory confidence intervals; frequentist theory of estimation including hypothesis tests; methods of inference based on likelihood theory, including use of Fisher and observed information and likelihood ratio; Wald and score tests; an introduction to the Bayesian approach to inference; an introduction to distribution-free statistical methods.
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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: |
Two written assignments to be submitted during semester worth 35% each (approx 10 hrs work each). Submission of selected practical exercises throughout the semester worth 10% each (approx 6 hrs work each). |
| Prescribed Texts: |
Marschner IC. Inference Principles for Biostatisticians. Chapman & Hall / CRC Press, 2014.
Printed course notes and assignment material by mail, email, and online interaction facilities. Special Computer Requirements: SAS or Stata Statistical Software
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| 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://mspgh.unimelb.edu.au/ |
| Notes: |
This subject is not available in the Master of Public Health.
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| Related Course(s): |
Graduate Certificate in Biostatistics Postgraduate Diploma in Biostatistics |
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