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Experimental Design and Data Analysis (MAST10011)
Undergraduate level 1Points: 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
Email: yaoban@unimelb.edu.au
Semester 2
Please refer to the LMS for up-to-date subject information, including assessment and participation requirements, for subjects being offered in 2020.
Overview
Availability(Quotas apply) | Semester 1 Semester 2 |
---|---|
Fees | Look up fees |
This subject provides an understanding of the fundamental concepts of probability and statistics required for experimental design and data analysis in the health sciences. Initially the subject introduces common study designs, random sampling and randomised trials as well as numerical and visual methods of summarising data. It then focuses on understanding population characteristics such as means, variances, proportions, risk ratios, odds ratios, rates, prevalence, and measures used to assess the diagnostic value of a clinical test. Finally, after determining the sampling distributions of some common statistics, confidence intervals will be used to estimate these population characteristics and statistical tests of hypotheses will be developed. The presentation and interpretation of the results from statistical analyses of typical health research studies will be emphasised.
The statistical methods will be implemented using a standard statistical computing package and illustrated on applications from the health sciences.
Intended learning outcomes
On completion of the subject, students should be able to:
- analyse standard data sets, interpreting the results of such analysis and presenting the conclusions in a clear and comprehensible manner;
- understand a range of standard statistical methods which can be applied to biomedical sciences.
- use a statistical computing package to analyse biomedical data;
- choose a form of epidemiological experimental design suitable for a range of standard biomedical experiments.
Generic skills
In addition to learning specific skills that will assist students in their future careers in the health sciences, they will have the opportunity to develop, generic skills 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: 31 October 2023
Eligibility and requirements
Prerequisites
None
Corequisites
None
Non-allowed subjects
Students may only gain credit for one of:
-
Code Name Teaching period Credit Points MAST10010 Data Analysis 1 Semester 2 (On Campus - Parkville)12.5 -
Code Name Teaching period Credit Points MAST10011 Experimental Design and Data Analysis Semester 1 (On Campus - Parkville)Semester 2 (On Campus - Parkville)12.5 -
Code Name Teaching period Credit Points ECON10005 Quantitative Methods 1 Semester 1 (On Campus - Parkville)Semester 2 (On Campus - Parkville)12.5
Students who have completed
Code | Name | Teaching period | Credit Points |
---|---|---|---|
MAST20005 | Statistics |
Semester 2 (On Campus - Parkville)
Summer Term (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: 31 October 2023
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 |
---|---|---|
1 Hand-written assignments (part 1) with use of software | From Week 3 to Week 4 | 5% |
1 Hand-written assignments (part 2) with use of software | From Week 7 to Week 8 | 5% |
One computer-based in-class test
| Week 11 | 10% |
Best 10 (of 11) online quizzes | Weekly from week 2 | 10% |
A written examination
| During the examination period | 70% |
Last updated: 31 October 2023
Quotas apply to this subject
Dates & times
- Semester 1
Principal coordinator Yao-Ban Chan Mode of delivery On Campus (Parkville) Contact hours 3 x one hour lectures per week, 1 x one hour practice class per week, 1 x one hour computer laboratory class 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
Email: yaoban@unimelb.edu.au
- Semester 2
Principal coordinator Paul Fijn Mode of delivery On Campus (Parkville) Contact hours 3 x one hour lectures per week, 1 x one hour practice class per week, 1 x one hour computer laboratory class per week Total time commitment 170 hours Teaching period 3 August 2020 to 1 November 2020 Last self-enrol date 14 August 2020 Census date 21 September 2020 Last date to withdraw without fail 16 October 2020 Assessment period ends 27 November 2020 Semester 2 contact information
Time commitment details
Estimated total time commitment of 170 hours
Additional delivery details
An enrolment quota of 350 students applies per semester. Students will be enrolled in Experimental Design and Data Analysis in the opposite semester to which they are enrolled in Mathematics for Biomedicine. Please refer to the Handbook entry for MAST10016 Mathematics for Biomedicine for further information.
Last updated: 31 October 2023
Further information
- Texts
Prescribed texts
None.
Recommended texts and other resources
B. Rosner, Fundamentals of Biostatistics, 8th Edition, Cengage Learning, 2015.
- Subject notes
This subject is only available to students enrolled in the Bachelor of Biomedicine degree or the Bachelor of Biomedical Science (pre-2008 degree)
- Related Handbook entries
This subject contributes to the following:
Type Name Course Bachelor of Biomedicine - 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 October 2023