Prerequisites
None
Time commitment
8-12 hours total study time per week
Semester availability
Semester 1 & 2
Assessment
Three written assignments worth 30%, 35% and 35%
Recommended Texts
If you have not used R or Stata previously, it is recommended that you have access to the text for the relevant software.
Hadley Wickham and Garrett Grolemund, R for Data Science: Import, Tidy, Transform, Visualize, and Model Data. O’Reilly Media, 2017.
Svend Juul and Morten Frydenberg. An Introduction to Stata for Health Researchers. Stata Press 2014
Special Computer Requirements
R and Stata software; RStudio is also strongly recommended.
Content
The topics covered are:
- Module 1 – Stata and R: The basics (importing and exporting data, recoding 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)
- 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
Resources
Course notes, online mini-lecture videos, online tutorials, discussion board