Module overview
This module will provide an introduction to time series models in common use and their use for predicting future observations and/or estimating unobservable components like trend and seasonal effects.
Linked modules
Pre-requisite: STAT6095
Aims and Objectives
Learning Outcomes
Learning Outcomes
Having successfully completed this module you will be able to:
- Decompose a time series into trend, seasonal and irregular components
- Understand and be able to apply the concepts and methods underlying the analysis of univariate time series, and the context for interpretation of results
- Understand the theoretical bases of different methods of time series analysis including decomposition
- Determine how and when to apply different methods of time series analysis and how to test for goodness of fit using the software package X12
Syllabus
- Difference of time series data compared to other data sets (equidistant observations, calendar effects, outliers)
- Basic concepts of time series: Stationarity, Ergodicity, Autocorrelations, Partial Autocorrelations
- Global models for trends and seasonals
- The periodogram and spectral analysis
- Local models and moving average methods
- ARIMA modelling and forecasting
- Exponential smoothing
- Estimation of unobservable components using a software package (X12ARIMA)
Learning and Teaching
Teaching and learning methods
.
| Type | Hours |
|---|---|
| Teaching | 34 |
| Independent Study | 66 |
| Total study time | 100 |
Resources & Reading list
General Resources
Laboratory space and equipment required. Practical computing lab in X12ARIMA
Textbooks
Harvey, A.C. (1989). Forecasting Structural Time Series Models and the Kalman Filter. Cambridge University Press.
Chatfield, C. (1996). The Analysis of Time Series: An Introduction. Chapman & Hall.
Wei, W. S. (1994). Time Series Analysis: Univariate and Multivariate Methods. Addison-Wesley Publishing company.
Harvey, A.C. (1993). Time Series Models.
Assessment
Summative
This is how we’ll formally assess what you have learned in this module.
| Method | Percentage contribution |
|---|---|
| Coursework | 100% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
| Method | Percentage contribution |
|---|---|
| Coursework assignment(s) | 100% |
Repeat
An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.
| Method | Percentage contribution |
|---|---|
| Coursework assignment(s) | 100% |
Repeat Information
Repeat type: Internal & External