Handbook home
Statistics (MAST20005)
Undergraduate level 2Points: 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 |
---|---|
Fees | Look up fees |
This subject introduces the theory underlying modern statistical inference and statistical computation. In particular, it demonstrates that many commonly used statistical procedures arise as applications of a common theory. Both classical and Bayesian statistical methods are developed. Basic statistical concepts including maximum likelihood, sufficiency, unbiased estimation, confidence intervals, hypothesis testing and significance levels are discussed. Applications include distribution free methods, goodness of fit tests, correlation and regression; the analysis of one-way and two-way classifications.
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 probability 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: 22 March 2024
Eligibility and requirements
Prerequisites
One of
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 |
Corequisites
None
Non-allowed subjects
Passing this subject (MAST20005 Statistics) precludes subsequent credit for either of
Code | Name | Teaching period | Credit Points |
---|---|---|---|
MAST10010 | Data Analysis 1 | Semester 2 (On Campus - Parkville) |
12.5 |
MAST10011 | Experimental Design and Data Analysis |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - 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: 22 March 2024
Assessment
Additional details
Three written assignments due at regular intervals during semester amounting to a total of up to 50 pages (20%), a 45-minute computer laboratory test held at the end of semester (10%), and a 3-hour written examination in the examination period (70%).
Last updated: 22 March 2024
Dates & times
- Semester 2
Principal coordinator Damjan Vukcevic Mode of delivery On Campus (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 24 July 2017 to 22 October 2017 Last self-enrol date 4 August 2017 Census date 31 August 2017 Last date to withdraw without fail 22 September 2017 Assessment period ends 17 November 2017 Semester 2 contact information
Time commitment details
Estimated total time commitment of 170 hours
Last updated: 22 March 2024
Further information
- Texts
Prescribed texts
R. Hogg, E. Tanis, and D. Zimmerman, Probability and Statistical Inference. 9th Edition, Pearson, 2015.
- 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 Statistics / Stochastic Processes Informal specialisation Science-credited subjects - new generation B-SCI and B-ENG. Informal specialisation Environments Discipline subjects Informal specialisation Selective subjects for B-BMED Major Statistics / Stochastic Processes Major Environmental Science Breadth Track Mathematics for Economics - Breadth options
This subject is available as breadth in the following courses:
- 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: 22 March 2024