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 the theoretical bases of different methods of time series analysis including decomposition
- Understand and be able to apply the concepts and methods underlying the analysis of univariate time series, and the context for interpretation of results
- 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
Chatfield, C. (1996). The Analysis of Time Series: An Introduction. Chapman & Hall.
Harvey, A.C. (1989). Forecasting Structural Time Series Models and the Kalman Filter. Cambridge University Press.
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