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Elements of Statistics (MAST90058)
Graduate courseworkPoints: 12.5On Campus (Parkville)
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Semester 2
Overview
Availability | Semester 2 |
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Fees | Look up fees |
The analysis of data arising in Bioinformatics and Biostatistics requires the use of sophisticated statistical techniques and computing packages. This subject introduces the theory underlying modern statistical inference and statistical computation. Both classical and Bayesian statistical methods are developed and many standard statistical methods are included as applications of a common theory. This subject is co-taught with MAST20005 Statistics.
Intended learning outcomes
- Students completing this subject should be familiar with the basic ideas of estimation and hypothesis testing and be able to carry out many standard statistical procedures using a statistical computing package.
- Students should develop the ability to fit probability models to data by both estimating and testing hypotheses about model parameters.
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: 3 November 2022
Eligibility and requirements
Prerequisites
One of the following, or equivalent:
Code | Name | Teaching period | Credit Points |
---|---|---|---|
MAST20004 | Probability | Semester 1 (On Campus - Parkville) |
12.5 |
MAST20006 | Probability for Statistics | Semester 1 (On Campus - Parkville) |
12.5 |
MAST90057 | Elements of Probability | Semester 1 (On Campus - Parkville) |
12.5 |
Corequisites
None
Non-allowed subjects
Students who have taken second year level subjects in Statistics or its equivalent may not take 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: 3 November 2022
Assessment
Additional details
30 pages of written assignments due during the semester (20%); a 45-minute computer laboratory test held mid-semester (10%); a 3-hour written examination in the examination period (70%).
Last updated: 3 November 2022
Dates & times
- Semester 2
Principal coordinator Damjan Vukcevic Mode of delivery On Campus (Parkville) Contact hours 36 hours: Three 1-hour lectures per week, one 1-hour tutorials per week, and one 1-hour computer laboratory classes per week. Total time commitment 170 hours Teaching period 23 July 2018 to 21 October 2018 Last self-enrol date 3 August 2018 Census date 31 August 2018 Last date to withdraw without fail 21 September 2018 Assessment period ends 16 November 2018 Semester 2 contact information
Time commitment details
170 hours
Last updated: 3 November 2022
Further information
- Texts
Prescribed texts
R. Hogg, E. Tanis, and D. Zimmerman, Probability and Statistical Inference. 9th Edition, Pearson, 2015.
- Subject notes
Students undertaking this subject are required to regularly use computers with the statistics package R installed.
Students undertaking this subject are not assumed to have any special computer skills at the beginning. They will learn the basic skills of using R in the subject.
- Related Handbook entries
This subject contributes to the following:
Type Name Course Master of Philosophy - Engineering Course Master of Commerce (Finance) Course Master of Science (Bioinformatics) Course Doctor of Philosophy - Engineering Course Ph.D.- 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.
Last updated: 3 November 2022