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Statistics (MAST20005)
Undergraduate level 2Points: 12.5Dual-Delivery (Parkville)
From 2023 most subjects will be taught on campus only with flexible options limited to a select number of postgraduate programs and individual subjects.
To learn more, visit COVID-19 course and subject delivery.
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Summer Term
Semester 2
Overview
| Availability | Summer Term - Dual-Delivery Semester 2 - Dual-Delivery |
|---|---|
| Fees | Look up fees |
This subject introduces the basic elements of statistical modelling, computation and data analysis. It is an entry point to further study of both mathematical and applied statistics, as well as broader data science.
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 and Bayesian inference. Applications covered include: exploratory data analysis, inference for samples from univariate distributions, simple linear regression, correlation, goodness-of-fit tests and analysis of variance.
Intended learning outcomes
Students completing this subject should be able to:
- Demonstrate an understanding of the basic ideas of estimation and hypothesis testing;
- Carry out many standard statistical procedures using a statistical computing package;
- 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 September 2023
Eligibility and requirements
Prerequisites
One of
| Code | Name | Teaching period | Credit Points |
|---|---|---|---|
| MAST20004 | Probability |
Semester 1 (Dual-Delivery - Parkville)
Semester 2 (Dual-Delivery - Parkville)
|
12.5 |
| MAST20006 | Probability for Statistics | Semester 1 (Dual-Delivery - Parkville) |
12.5 |
Corequisites
Non-allowed subjects
Passing this subject (MAST20005 Statistics) precludes subsequent credit for:
| Code | Name | Teaching period | Credit Points |
|---|---|---|---|
| MAST10010 | Data Analysis 1 | Semester 2 (Dual-Delivery - Parkville) |
12.5 |
| MAST10011 | Experimental Design and Data Analysis | Semester 1 (Dual-Delivery - Parkville) |
12.5 |
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 September 2023
Assessment
Semester 2
| 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% |
Summer Term
| Description | Timing | Percentage |
|---|---|---|
Two 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 September 2023
Dates & times
- Summer Term
Principal coordinator Liuhua Peng Mode of delivery Dual-Delivery (Parkville) Contact hours Summer semester: 6 x 1 hour lectures per week, 2 x one hour practice classes per week, and 2 x one hour computer laboratory classes per week. Semester 2: 3 x one hour lectures per week, 1 x one hour practice class per week, and 1 x one hour computer laboratory class per week Total time commitment 170 hours Teaching period 4 January 2022 to 15 February 2022 Last self-enrol date 12 January 2022 Census date 21 January 2022 Last date to withdraw without fail 4 February 2022 Assessment period ends 25 February 2022 Summer Term contact information
- Semester 2
Coordinator Damjan Vukcevic Mode of delivery Dual-Delivery (Parkville) Contact hours 3 x one hour lectures per week, 1 x one hour practice class per week, and 1 x one-hour computer laboratory class per week Total time commitment 170 hours Teaching period 25 July 2022 to 23 October 2022 Last self-enrol date 5 August 2022 Census date 31 August 2022 Last date to withdraw without fail 23 September 2022 Assessment period ends 18 November 2022 Semester 2 contact information
Time commitment details
Estimated total time commitment of 170 hours
Last updated: 7 September 2023
Further information
- Texts
Prescribed texts
None
- Subject notes
This subject is available for science credit to students enrolled in the BSc (both pre-2008 and new degrees), BASc or a combined BSc course.
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 Informal specialisation Science Discipline subjects - new generation B-SCI Major Environmental Science Informal specialisation Environments Discipline subjects Major Statistics / Stochastic Processes Informal specialisation Statistics / Stochastic Processes Breadth Track Mathematics for Economics - Breadth options
This subject is available as breadth in the following courses:
- Bachelor of Arts
- Bachelor of Commerce
- Bachelor of Design
- Bachelor of Environments
- Bachelor of Fine Arts (Acting)
- Bachelor of Fine Arts (Animation)
- Bachelor of Fine Arts (Dance)
- Bachelor of Fine Arts (Film and Television)
- Bachelor of Fine Arts (Music Theatre)
- Bachelor of Fine Arts (Production)
- Bachelor of Fine Arts (Screenwriting)
- Bachelor of Fine Arts (Theatre)
- Bachelor of Fine Arts (Visual Art)
- Bachelor of Music
- 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 September 2023