Overview
MATH5901 is a Honours and Postgraduate Coursework Mathematics course. See the聽course overview聽below
Units of credit:听6
Prerequisites:聽(MATH2501 or MATH2601) and (MATH2011 or MATH2111) and (MATH2801 or MATH2901), or admitted to a Postgraduate Mathematics or Statistics program.
Exclusion:聽MATH3801 or MATH3901 (jointly taught with MATH5901)聽
Cycle of offering:聽T1 2023聽
Graduate attributes:聽The course will enhance your research, inquiry and analytical thinking abilities.聽This course aims to introduce some of the basic ideas and tools of the theory of stochastic processes. The theory of stochastic processes deals with phenomena evolving randomly in time and/or space, such as prices on financial markets, air temperature or wind velocity, spread of diseases, number of hospital admissions in certain area, and many others.
More information:聽The Course outline will be made available closer to the start of term - please visit this website: www.unsw.edu.au/course-outlines
The聽Course Outline聽provides information about course objectives, assessment, course materials and the syllabus.
Important additional information as of 2023
UNSW Plagiarism Policy
The University requires all students to be aware of its聽.
For courses convened by the聽School of Mathematics and Statistics no assistance using generative AI software is allowed unless specifically referred to in the individual assessment tasks.
If its use is detected in the no assistance case, it will be regarded as serious academic misconduct and subject to the standard penalties, which may include 00FL, suspension and exclusion.
The entry contains information about the course. The timetable is only up-to-date if the course is being offered this year.
If you are currently enrolled in聽MATH5901, you can log into聽聽for this course.
Course overview
This course introduces some of the basic ideas and tools to study such phenomena. In particular, we will introduce Markov Chains (both in discrete and continuous time), Poisson processes, Brownian motion and Martingales.
The course will also cover other important but less routine topics, like Markov decision processes and some elements of queueing theory.