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