Variability, randomness, risk, and related attributes characterise most measurable phenomena in the real world. Probability and Stochastic Processes are concerned with random phenomena occurring dynamically in time, space, or both. They play a critical role in the theory and methods of a wide range of physical, medical, engineering and social sciences, and many others. A good understanding of probability is essential for the study of Statistics. Probability theory is both mathematically elegant and remarkably practical, and the distinction it makes between deterministic and stochastic modelling is fundamental to real-world applications, especially in the areas of insurance risk, genetics and evolutionary biology, climatology, epidemiology, criminology, time series modelling and forecasting, signal processing and detection, and derivatives pricing and financial mathematics.
Learning Outcomes
- Explain the fundamental concepts of probability theory and its position in modern statistical and mathematical sciences and applied contexts.
- Explain the fundamental concepts of stochastic processes in continuous time and their position in modern statistical and mathematical sciences and applied contexts.
- Using a diverse range of discipline backgrounds and varied data, communicate the role of generalized linear modelling techniques (GLMs) in modern applied statistics and implement GLM methodology.
- Solve complex problems relating to probability theory and stochastic processes in a variety of discipline backgrounds.
- Use stochastic calculus in mathematical and financial problems.
Other Information
Students who are not enrolled in the BSTAT degree undertaking this major will need to complete the following courses to be able to complete the 48 units of this major:
- MATH1115 OR MATH1113
- MATH1116 (MATH1116 is only required if MATH1113 not completed)
- STAT1003 OR STAT1008
- STAT2001 OR STAT2013
- STAT2005
Requirements
This major requires the completion of 48 units, which must include:
18 units from completion of the following compulsory courses:
STAT3004 Stochastic Processes
STAT3006 Advanced Stochastic Processes
STAT3015 Generalised Linear Models
6 units from completion of the following list:
An additional course from the subject area STAT Statistics
MATH3015 Stochastic Analysis with Financial Applications
MATH3029 Probability Theory with Applications
Either:
24 units from completion of the following mathematical statistics courses:
MATH2305 Applied Mathematics I
MATH2306 Applied Mathematics II
STAT3013 Statistical Inference
STAT3056 Advanced Mathematical Statistics
Or:
24 units from completion of the following courses:
MATH2320 Advanced Analysis 1: Metric Spaces and Applications
MATH3320 Advanced Analysis 2: Lebesgue Integration and Hilbert Spaces
STAT3017 Big Data Statistics
6 units from completion of further courses from the subject area STAT Statistics
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