Minor Overview
- About this minor
- The minor provides students with a sequence of statistical units in data science which starts with basic ideas in data science and ends with sophisticated (third-year) methods in modern statistical learning, computational statistics and data analysis. These approaches will equip the students with statistical and computational skills to find appropriate data analysis solutions to problems in a diverse range of areas including the physical sciences, medical and biological sciences, engineering, business and social sciences. For students taking a minor which shares units with their other unit sets (majors or minors): in order for minors to be recognised on academic and graduation documents, students may only have a maximum of one unit overlapping between their unit sets.
- Outcomes
- Students are able to (1) apply the basic concepts and methods of statistical learning; (2) use suitable software to analyse data
; (3) identify appropriate supervised or unsupervised approaches for specific data and problems; (4) critically assess the suitability of a specific approach for solving a particular data science problem; (5) interpret the results of an analysis; and (6) communicate the results of an analysis in verbal and written form for non-experts.. - Incompatibility
MJD-DATSC Data Science;
MJD-CDSDM Computing and Data Science;
MJD-HSDEM Human Sciences and Data Analytics;
MNR-DATSC Data Science
Units
Key to availability of units:
- S1
- Semester 1
- S2
- Semester 2
Take the following unit:
Availability | Unit code | Unit name | Unit requirements |
---|---|---|---|
S1, S2 | STAT1400 | Statistics for Science |
Take all units (12 points):
Availability | Unit code | Unit name | Unit requirements |
---|---|---|---|
S1 | STAT2401 | Analysis of Experiments | |
S2 | STAT2402 | Analysis of Observations |
Take the following unit:
Availability | Unit code | Unit name | Unit requirements |
---|---|---|---|
S1 | STAT3406 | Applied Statistics and Data Visualisation |
|