• Offered by Rsch Sch of Finance, Actuarial Studies & App Stats
• ANU College ANU College of Business and Economics
• Course subject Statistics
• Areas of interest Actuarial Studies, Finance, Statistics
• Course convener
• Dr Soudabeh Shemehsavar
• Mode of delivery In Person
• Co-taught Course
• Offered in Second Semester 2019
Introduction to Stochastic Processes (STAT7004)

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:

On satisfying the requirements for this course, students will have the knowledge and skills to:
1 Demonstrate the concepts and investigation of the long-run behavior, respectively, of simple stochastic processes in discrete time; namely, Markov chains.
2 Demonstrate in detail the various topics of continuous-time stochastic processes, with topics drawn from:
a Poisson Processes
b other Markov pure jump processes
c Brownian motion
d Other related Gaussian processes

## Indicative Assessment

Typical assessment may include, but is not restricted to: quizzes, mid-semester examination and a final examination.

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.

## Requisite and Incompatibility

To enrol in this course you must have completed STAT6039 or STAT6013. Incompatible with STAT2005.

## 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.

If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.

Student Contribution Band:
2
Unit value:
6 units

If you are an undergraduate student and 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). You can find your student contribution amount for each course 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
2019 \$3840
International fee paying students
Year Fee
2019 \$5460
Note: Please note that fee information is for current year only.

## 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.

The list of offerings for future years is indicative only.
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
9068 22 Jul 2019 29 Jul 2019 31 Aug 2019 25 Oct 2019 In Person View