Available in 2024
Course code

STAT3040

Units

10 units

Level

3000 level

Course handbook

Description

Time series analysis is a statistical methodology to exploit historical data generated by real world systems to forecast the future of these systems. This course presents both theory and applications of time series analysis at a level accessible to a wide variety of students and practitioners in statistics, economics and finance, science, engineering and quantitative social sciences. Emphasis is placed on the development and choice of appropriate models, how to estimate and test model parameters and forecast future values.


Availability2024 Course Timetables

Callaghan

  • Semester 2 - 2024

Learning outcomes

On successful completion of the course students will be able to:

1. Explain the concepts of time series analysis in the time domain;

2. Identify and apply appropriate models for the real life datasets;

3. Have developed skills in statistical computing of time series problems.


Content

  • Introduction and Review
  • Fundamental concepts in Time Series (TS)
  • Model Stationary TS
  • Model Nonstationary TS
  • Model specification TS
  • Model estimation TS
  • Model diagnostics TS
  • Model forecasting TS

Assumed knowledge

STAT1070 or STAT1300 or STAT2110


Assessment items

Written Assignment: Written assignments

Project: Project

Online Open Book Formal Examination: Final Examination


Contact hours

Semester 2 - 2024 - Callaghan

Computer Lab-1
  • Face to Face On Campus 2 hour(s) per week(s) for 12 week(s)
Lecture-1
  • Face to Face On Campus 2 hour(s) per week(s) for 13 week(s) starting in week 1

Course outline

Course outline not yet available.