Applied Statistical Learning 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.

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..

Unit sequence

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
Prerequisites:
Mathematics Applications ATAR
or
MATH1720 Mathematics Fundamentals
or
equivalent
or
higher
Incompatibility:
STAT1520 Economic and Business Statistics
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
S2 STAT3406 Applied Statistics and Data Visualisation
Prerequisites:
MATH1012 Mathematical Theory and Methods
or
STAT2401 Analysis of Experiments (ID 390)