This course involves on campus teaching. For students unable to come to campus there will be a remote option. See the Class Summary for more details.
An introduction to stochastic processes, which are random processes occurring in time or space.
They are used to model dynamic relationships involving random events in a wide variety of disciplines including the natural and social sciences, and in financial, managerial and actuarial settings.
The course consists of a short review of basic probability concepts and a discussion of conditional probability and conditional expectation, followed by an introduction to the basic concepts and an investigation of the long-run behaviour of Markov chains in discrete time, countable state space. The course also covers some important continuous-time stochastic processes including Poisson processes and other Markov pure jump processes, as well as Brownian motion and other related Gaussian processes as time permits.
Learning Outcomes
Upon successful completion, students will have the knowledge and skills to:
- Decsribe in detail the basic concepts of stochastic processes in discrete time, especially concerning Markov chains, their classifications and long-run behaviour; and
- Explain in detail continuous-time stochastic processes, with topics drawn from: Poisson Processes other Markov pure jump processes Brownian motion Other related Gaussian processes
Indicative Assessment
- Typical assessment may include, but is not restricted to: exams, assignments, quizzes, presentations and other assessment as appropriate (100) [LO 1,2]
The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.
Workload
Students are expected to commit 130 hours of work in completing this course. This includes time spent in scheduled classes and self-directed study time.
Inherent Requirements
Not applicable
Requisite and Incompatibility
Prescribed Texts
Information about the prescribed textbook will be available via the Class Summary
Assumed Knowledge
Students will require a good background in introductory mathematical statistics and probability concepts, including random variables, probability distributions, etc.Fees
Tuition fees are for the academic year indicated at the top of the page.
Commonwealth Support (CSP) Students
If you have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). More information about your student contribution amount for each course at Fees.
- Student Contribution Band:
- 1
- Unit value:
- 6 units
If you are a domestic graduate coursework student with a Domestic Tuition Fee (DTF) place or international student you will be required to pay course tuition fees (see below). Course tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.
Where there is a unit range displayed for this course, not all unit options below may be available.
| Units | EFTSL |
|---|---|
| 6.00 | 0.12500 |
Course fees
- Domestic fee paying students
| Year | Fee |
|---|---|
| 2022 | $4200 |
- International fee paying students
| Year | Fee |
|---|---|
| 2022 | $6000 |
Offerings, Dates and Class Summary Links
ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.
Second Semester
| Class number | Class start date | Last day to enrol | Census date | Class end date | Mode Of Delivery | Class Summary |
|---|---|---|---|---|---|---|
| 5850 | 25 Jul 2022 | 01 Aug 2022 | 31 Aug 2022 | 28 Oct 2022 | In Person | View |
