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Elements of Statistics (MAST90058)
Graduate courseworkPoints: 12.5On Campus (Parkville)
From Semester 1, 2023 our undergraduate programs will be delivered on campus. Graduate programs will mainly be delivered on campus, with dual-delivery and online options available to a select number of subjects within some programs.
To learn more, visit 2023 Course and subject delivery.
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 |
|---|---|
| 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 basic elements of statistical modelling, computation and data analysis. Students will develop the ability to fit statistical models to data, estimate parameters of interest and test hypotheses. Both classical and Bayesian approaches will be covered. The importance of the underlying mathematical theory of statistics and the use of modern statistical software will be emphasised.
Concepts covered include: descriptive statistics, random sample, statistical inference, point estimation, interval estimation, properties of estimators, maximum likelihood, confidence intervals, hypothesis testing, Bayesian inference. Applications covered include: exploratory data analysis, inference for samples from univariate distributions, simple linear regression, correlation, goodness-of-fit tests, analysis of variance.
The lectures in this subject are co-taught with MAST20005 Statistics; the practice classes are separate.
Intended learning outcomes
Students completing this subject should:
- Be familiar with the basic ideas of estimation and hypothesis testing
- Be able to carry out many standard statistical procedures using a statistical computing package
- Develop the ability to fit statistical models to data by both estimating and testing hypotheses about model parameters.
Generic skills
In addition to learning specific skills that will assist students in their future careers in science, they should progressively acquire generic skills from this subject that will assist them in any future career path. 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
- Computer skills: the ability to use statistical computing packages.
Last updated: 7 March 2023
Eligibility and requirements
Prerequisites
One of
| Code | Name | Teaching period | Credit Points |
|---|---|---|---|
| MAST20004 | Probability |
Semester 2 (On Campus - Parkville)
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 |
Or equivalent
Corequisites
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: 7 March 2023
Assessment
| Description | Timing | Percentage |
|---|---|---|
Three written assignments due at regular intervals amounting to a total of up to 50 pages
| During the teaching period | 20% |
A computer laboratory test
| End of the teaching period | 10% |
A written examination
| During the examination period | 70% |
Last updated: 7 March 2023
Dates & times
- Semester 2
Coordinator Robert Maillardet 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 24 July 2023 to 22 October 2023 Last self-enrol date 4 August 2023 Census date 31 August 2023 Last date to withdraw without fail 22 September 2023 Assessment period ends 17 November 2023 Semester 2 contact information
Time commitment details
170 hours
What do these dates mean
Visit this webpage to find out about these key dates, including how they impact on:
- Your tuition fees, academic transcript and statements.
- And for Commonwealth Supported students, your:
- Student Learning Entitlement. This applies to all students enrolled in a Commonwealth Supported Place (CSP).
- Completion rate. Students who started their course from 2022 and are in a CSP or receiving a HELP Loan (eg FEE-HELP) must meet the completion rate to continue to receive Commonwealth Support for that course.
Subjects withdrawn after the census date (including up to the ‘last day to withdraw without fail’) count toward the Student Learning Entitlement, and as a fail toward the completion rate, unless there are approved ‘special circumstances’.
Last updated: 7 March 2023
Further information
- Texts
Prescribed texts
There are no specifically prescribed or recommended texts for this subject.
- 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 Commerce (Finance) Course Master of Philosophy - Engineering Course Ph.D.- Engineering Course Doctor of Philosophy - Engineering Course Master of Science (Bioinformatics) - 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: 7 March 2023