Introduction to Statistical Computing (MAST90101)
Graduate courseworkPoints: 12.5Dual-Delivery (Parkville)
About this subject
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 |
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Fees | Look up fees |
The aim of this subject is to equip students with the knowledge and skills required for moderate to high level data manipulation and management in preparation for statistical analysis of data typically encountered in health and medical research. Students will gain hands-on experience with two major statistical software packages (Stata and R), learning to efficiently manage and manipulate data, display and summarize data, check and clean datasets, and link files using unique and non-unique identifiers. Additionally, students will acquire fundamental graphing and programming skills for each of these software packages and will be introduced to key principles of confidentiality and privacy in data storage, management, and analysis.
Intended learning outcomes
On completion of the subject, students should be able to:
- Gain experience in data manipulation and management using two major statistical software packages (Stata and R).
- Display and summarise data using statistical software.
- Perform checks and clean datasets to ensure data integrity.
- Apply programming skills to link files through the use of unique and non-unique identifiers.
- Demonstrate fundamental programming skills for efficient use of software packages.
- Recognise 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: 4 March 2025