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Introduction to Statistical Computing (MAST90101)
Graduate courseworkPoints: 12.5Dual-Delivery (Parkville)
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable (login required)(opens in new window)
Contact information
Semester 1
emily.karahalios@unimelb.edu.au
Currently enrolled students:
- General information: https://ask.unimelb.edu.au
- Email: Contact Stop 1
Future Students:
- Further Information: https://study.unimelb.edu.au/
Overview
| Availability | Semester 1 - Dual-Delivery |
|---|---|
| Fees | Look up fees |
The aim of this subject is to provide students with the knowledge and skills required to undertake moderate to high level data manipulation and management in preparation for statistical analysis of data typically arising in health and medical research. In particular, students gain experience in data manipulation and management using two major statistical software packages (Stata and R) and acquire fundamental programme skills for efficient use of each of these software packages.
Intended learning outcomes
The specific learning outcomes are:
- Gain experience in data manipulation and management using two major statistical software packages (Stata and R).
- Learn how to display and summarise data using statistical software.
- Become familiar with the checking and cleaning of data.
- Learn how to link files through use of unique and non-unique identifiers.
- Acquire fundamental programming skills for efficient use of software packages.
- Learn key principles regarding confidentiality and privacy in data storage, management and analysis.
Generic skills
- Independent problem solving,
- Facility with abstract reasoning,
- Clarity of written expression,
- Sound communication of technical concepts
Last updated: 22 February 2024