Subject description
A crucial skill in data science is the management and organisation of data. Usually, the most time-consuming step in analyses is the setup and shaping of data for the required analyses.
Visualisation of data, whether used for exploratory analysis or for illustration of results, is a must in any translational … For more content click the Read More button below.
This subject will cover basics of reproducibility of research. The documenting of code scripts, dynamic document and analysis creation, and analysis/coding good practices will be covered. The subject will rely heavily on statistical packages such as R, RStudio and RMarkdown.
The subject will cover data wrangling, which involves reading in data sets from different sources, cleaning data, and aggregating and summarising variables and rows from data. This subject will also cover basics of administrative data use and existence of resources for accessing data.
Equivalence
STAT250 - Managing and Communicating Data
Delivery
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Teaching staff
Subject coordinators
Learning outcomes
On successful completion of this subject, students will be able to:
1.
Implement and perform data acquisition, reading, cleaning and wrangling of data.
2.
Plan and carry out data extraction from large and complex data sets.
3.
Learn to create code scripts that are well documented.
4.
Select and implement data visualisation methods appropriate for real-world projects and applications.
5.
Create dynamic documents that incorporate text, code, and visualisations.
6.
Interpret and communicate with a narrative results from analyses.