2 x 1-hour lectures weekly
1 x 2-hour tutorial weekly
Enrolment not permitted
STAT3702 has been successfully completed
Assumed knowledge
Knowledge of the principles of the theory of probability and applied probability modelling such as can be obtained in the topic STAT2702 Probability.
Topic description

Introduction to Stochastic Processes; Markov Chains; Fundamental concepts in Time Series; Model Stationary and Nonstationary; Model specification; Model estimation; Model diagnostics and Model forecasting in Time Series.

Educational aims

This topic aims to build upon the principles of applied probability modelling to extend to models of complex processes.

Expected learning outcomes
On completion of this topic you will be expected to be able to:

  1. Understand the concepts of stochastic processes and time series analysis in the time domain respectively
  2. Determine and apply appropriate time series models for the real life datasets
  3. Have developed skills in statistical computing of time series or stochastic processes related problems
  4. Have developed knowledge of the research principles and methods applicable in time series research project

Key dates and timetable

(1), (2)

Each class is numbered in brackets.
Where more than one class is offered, students normally attend only one.

Classes are held weekly unless otherwise indicated.


If you are enrolled for this topic, but all classes for one of the activities (eg tutorials) are full,
contact your College Office for assistance. Full classes frequently occur near the start of semester.

Students may still enrol in topics with full classes as more places will be made available as needed.

If this padlock appears next to an activity name (eg Lecture), then class registration is closed for this activity.

Class registration normally closes at the end of week 2 of each semester.

Classes in a stream are grouped so that the same students attend all classes in that stream.
Registration in the stream will result in registration in all classes.
  Unless otherwise advised, classes are not held during semester breaks or on public holidays.