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Elements of Probability (MAST90057)
Graduate courseworkPoints: 12.5On Campus (Parkville)
For information about the University’s phased return to campus and in-person activity in Winter and Semester 2, please refer to the on-campus subjects page.
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Semester 1
Please refer to the LMS for up-to-date subject information, including assessment and participation requirements, for subjects being offered in 2020.
Overview
Availability | Semester 1 |
---|---|
Fees | Look up fees |
Randomness is inherent in biological data and the analysis of data arising in both Bioinformatics and Biostatistics requires knowledge of sophisticated probability models and statistical techniques. This subject develops the underlying probability theory that is necessary to understand these models and techniques. Computer packages are used for numerical and theoretical calculations but no programming skills are required. Elements of Probability will be co-taught with MAST20006 Probability for Statistics.
Intended learning outcomes
At the completion of the subject, students are expected to:
- have developed a systematic understanding of probability, random variables, probability distributions and probability models, and their relevance to statistical inference;
- be able to formulate standard probability models from biological applications and critically assess them;
- be able to apply the properties of probability distributions, to analyse common random variables and probability models; and
- be able to use a computer package to perform algebraic and computational tasks in probability analyses.
Generic skills
These include:
- problem-solving skills: the ability to engage with unfamiliar problems and identify relevant solution strategies;
- analytical skills: the ability to construct and express logical arguments and to work in abstract or general terms to increase the clarity and efficiency of analysis;
- collaborative skills: the ability to work in a team;
- time management skills: the ability to meet regular deadlines while balancing competing commitments;
- become familiar with a major statistical computing package.
Last updated: 31 January 2024
Eligibility and requirements
Prerequisites
Code | Name | Teaching period | Credit Points |
---|---|---|---|
MAST10005 | Calculus 1 |
Semester 2 (On Campus - Parkville)
Semester 1 (On Campus - Parkville)
|
12.5 |
OR
Equivalent subject
OR
Admission into or selection of one of the following:
- MC-SCIBIF Master of Science (Bioinformatics)
- MC-COMPBIO Master of Computational Biology
Corequisites
None
Non-allowed subjects
Students who have previously taken second year level subjects in Probability or Probability for Statistics or their equivalents may not gain credit for this subject.
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: 31 January 2024
Assessment
Due to the impact of COVID-19, assessment may differ from that published in the Handbook. Students are reminded to check the subject assessment requirements published in the subject outline on the LMS
Description | Timing | Percentage |
---|---|---|
Written assignments
| During the teaching period | 20% |
A computer laboratory test
| During the teaching period | 10% |
A written examination
| During the examination period | 70% |
Last updated: 31 January 2024
Dates & times
- Semester 1
Principal coordinator Sophie Hautphenne Mode of delivery On Campus (Parkville) Contact hours 36 hours: Three x 1-hour lectures per week, one x 1-hour practice classes per week, and one x 1-hour computer laboratory classes per week. Total time commitment 170 hours Teaching period 2 March 2020 to 7 June 2020 Last self-enrol date 13 March 2020 Census date 30 April 2020 Last date to withdraw without fail 5 June 2020 Assessment period ends 3 July 2020 Semester 1 contact information
Time commitment details
170 hours
Last updated: 31 January 2024
Further information
- Texts
Prescribed texts
Hogg and Tanis, Probability and Statistical Inference. Eighth Edition, Prentice Hall, 2009.
- Related Handbook entries
This subject contributes to the following:
Type Name Course Master of Science (Bioinformatics) Course Master of Commerce (Finance) Course Doctor of Philosophy - Engineering Course Ph.D.- Engineering Course Master of Philosophy - Engineering - 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.
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
This subject is available to students studying at the University from eligible overseas institutions on exchange and study abroad. Students are required to satisfy any listed requirements, such as pre- and co-requisites, for enrolment in the subject.
Last updated: 31 January 2024