Statistics is data science. Through this major you will learn the tools that will empower the next generation of artificial intelligence, scientific inquiry, and predictive analytics for business and government. It will open you up to the exciting world of data science that is driving significant innovation in the world of start-ups and disrupting the socio-economic landscape. This degree will give you a rigorous mathematical and computational foundation in the areas of statistical learning (aka. machine learning), high-dimensional statistics, data visualisation, and the Bayesian approach that will help you build sophisticated models that capture the uncertainty in the world we live in.
Learning Outcomes
- Formulate statistical solutions to scientific, business, and policy questions while wrangling real world data, which may be messy, large, and complex.
- Visualise relationships among high dimensional and complex data (time and space).
- Demonstrate rigorous understanding of the mathematical and computational underpinnings of various statistical procedures.
- Explain and utilise the Bayesian framework for data analytics; appreciate when the Bayesian approach is beneficial.
- Demonstrate an understanding of the differences between the analysis of Big Data compared to the traditional small or medium scale data setting.
- Demonstrate the ability to evaluate the performance of various predictive models.
- Demonstrate the ability to analyse various data sets (messy, large, complex) in the statistical package R.
- Communicate complex statistical ideas and results to diverse audiences.
Other Information
Students will need to complete the following courses in order to be able to complete the 48 units of this major:
- MATH1013 OR MATH1115 OR MATH1113
- MATH1014 OR MATH1116 (MATH1014 or MATH1116 is only required if MATH1113 not completed)
- STAT1003 OR STAT1008
- STAT2001 OR STAT2013
- STAT2008 OR STAT2014
- COMP1100 OR COMP1130 OR COMP1730
Requirements
This major requires the completion of 48 units, which must consist of:
36 units from completion of the following compulsory courses:
STAT3011 Graphical Data Analysis
STAT3015 Generalised Linear Modelling
STAT3016 Introduction to Bayesian Data Analysis
STAT3017 Big Data Statistics
STAT3040 Statistical Learning
STAT3050 Advanced Statistical Learning
12 units from completion of computer science courses from the following list:
COMP1110 Structured Programming
COMP2400 Relational Databases
COMP2420 Introduction to Data Management, Analysis and Security
COMP3425 Data Mining
COMP3430 Data Wrangling
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