STAT3040
10 units
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.
The University of Newcastle acknowledges the traditional custodians of the lands within our footprint areas: Awabakal, Darkinjung, Biripai, Worimi, Wonnarua, and Eora Nations. We also pay respect to the wisdom of our Elders past and present.