Data Management and Statistical Computing

Postgraduate | 2026

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area/catalogue icon
Area/Catalogue
BIOL 5027
Course ID icon
Course ID
203053
Level of study
Level of study
Postgraduate
Unit value icon
Unit value
6
Course level icon
Course level
5
Study abroad and student exchange icon
Inbound study abroad and exchange
Inbound study abroad and exchange
The fee you pay will depend on the number and type of courses you study.
No
University-wide elective icon
University-wide elective course
No
Single course enrollment
Single course enrolment
No
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Note:
Course data is interim and subject to change

Course overview

The aim of this course is to provide students with 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. Content includes: Module 1 - Stata and R: The basics (importing and exporting data, recording data, formatting data, labelling variable names and data values; using dates, data display and summary presentation, and creating programs); Module 2 - Stata and R: graphs, data management and statistical quality assurance methods (including advanced graphics to produce publication-quality graphs) and Module 3 - Data management using Stata and R (using functions to generate new variables, appending, merging, transposing longitudinal data; programming skills for efficient and reproducible use of these packages, including loops and arguments).

Course learning outcomes

  • See Study Guides at: https://url.au.m.mimecastprotect.com/s/jyzMCmO5QMCjMl1XJtJi1URPVES?domain=bca.edu.au/
  • Be able to undertake data manipulation and management using two major statistical software packages (Stata and R)
  • Be able to appropriately display and summarise data using statistical software
  • Understand how to check and clean data
  • Be able to link data files through unique and non-unique identifiers
  • Have fundamental programming skills for efficient use of statistical software
  • Understand key principles of confidentiality and privacy in data storage, management and analysis

Prerequisite(s)

N/A

Corequisite(s)

N/A

Antirequisite(s)

N/A