Probability & Inference in Biostatistics (MAST90100)
Graduate courseworkPoints: 12.5Dual-Delivery (Parkville)
About this subject
Contact information
Semester 1
Melbourne School of Population and Global Health
OR
Currently enrolled students:
- General information: https://ask.unimelb.edu.au
- Email: Contact Stop 1
Future Students:
- Further Information: https://study.unimelb.edu.au/
Overview
| Availability | Semester 1 - Dual-Delivery |
|---|---|
| Fees | Look up fees |
This subject covers the fundamental theory of probability and statistical inference that is needed as a foundation for understanding and practice of the core methods of biostatistics, understood as the science of drawing conclusions from data in health and medical investigations. Major topics include fundamental concepts of probability and distributions, including simulation of hypothetical data, and key concepts of statistical estimation and hypothesis testing, including sampling variability, confidence intervals, likelihood functions and an introduction to the Bayesian approach to inference. The approach emphasizes a critical understanding of the role of statistical inference in health research.
Intended learning outcomes
On completion of this subject, students should be able to:
- Demonstrate an understanding of the fundamental concepts of probability, including discrete and continuous probability distributions
- Apply calculus-based techniques to derive key features of a probability distribution and properties of random variables, such as mean and variance
- Recognise common probability distributions and their properties
- Demonstrate the role of simulation of random variables in understanding and explaining random variation and key ideas of statistical inference
- Explain and employ the key elements of statistical inference: target parameters, sampling variability, and frequentist methods including confidence intervals and hypothesis testing
- Explain the role of the likelihood function in parametric statistical inference, and be able to derive and interpret likelihood-based estimates for standard models
- Explain Bayesian concepts of post-data uncertainty and derive Bayesian inferences for simple standard models
- Critically interpret the commonly used tools of statistical inference, such as p-values, confidence intervals and Bayesian posterior distributions, as they are used in medical and scientific investigations
Generic skills
- Independent problem solving,
- Facility with abstract reasoning,
- Clarity of written expression,
- Sound communication of technical concepts
Last updated: 22 November 2024
Eligibility and requirements
Prerequisites
None
Corequisites
None
Non-allowed subjects
None
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 22 November 2024
Assessment
| Description | Timing | Percentage |
|---|---|---|
Practical exercise 1
| Week 2 | 10% |
Major assignment 1
| Week 5 | 20% |
Major assignment 2
| Week 12 | 30% |
Written examination
| End of the teaching period | 40% |
Last updated: 22 November 2024
Dates & times
- Semester 1
Coordinator Marnie Downes Mode of delivery Dual-Delivery (Parkville) Contact hours Total time commitment 170 hours Teaching period 26 February 2024 to 26 May 2024 Last self-enrol date 8 March 2024 Census date 3 April 2024 Last date to withdraw without fail 3 May 2024 Assessment period ends 21 June 2024 Semester 1 contact information
Melbourne School of Population and Global Health
OR
Currently enrolled students:
- General information: https://ask.unimelb.edu.au
- Email: Contact Stop 1
Future Students:
- Further Information: https://study.unimelb.edu.au/
Time commitment details
170 hours
Last updated: 22 November 2024
Further information
- Texts
- Related Handbook entries
This subject contributes to the following:
Type Name Course Master of Biostatistics Course Graduate Diploma in Biostatistics - Available through the Community Access Program
About the Community Access Program (CAP)
This subject is available through the Community Access Program (also called Single Subject Studies) which allows you to enrol in single subjects offered by the University of Melbourne, without the commitment required to complete a whole degree.
Please note Single Subject Studies via Community Access Program is not available to student visa holders or applicants
Entry requirements including prerequisites may apply. Please refer to the CAP applications page for further information.
- Available to Study Abroad and/or Study Exchange Students
Last updated: 22 November 2024