Module fact file
- Masters Level
- Summer Term
- 10 credits
- Contact Hours:
- 13.00 - 15.30 (Over four days)
- Available to students who have taken Fundamentals in Quantitative Research Methods.
This module will introduce you to the analysis of time-series data using graphical and statistical techniques for model-fitting (regression). The emphasis is on the practical application of these research techniques while striking a balance between intuition, statistical rigour and practical use of statistical software. The module includes datasets that can be used to practice the statistical techniques taught on the course. The module material also includes all the commands needed to implement these statistical techniques using EViews, Gretl, R-project, SPSS and Stata.
On completion of the module, you should be able to:
- Understand the special features of time-series models in terms of the dynamic structures that may become apparent.
- Independently analyse time-series data using the statistical software EViews, Gretl, R-project, SPSS or Stata.
- Understand the key features that makes time-series regression different from cross-section regression. The possibility that the errors/residuals from the regression may be correlated across time.
- Distinguish between time-series data that are stationary (mean-reverting to an average value) and time-series data that are non-stationary (increasing or decreasing perpetually in time).
- Independently apply the basic techniques for including lagged values of the dependent and independent variables in time-series regression models.
- Apply the basic tests used to identify the presence of autocorrelation in the errors/residuals of a time-series regression.
- Understand the basic models used to accommodate the presence of autocorrelation in the errors/residuals in a time-series regression.
Technical report involving time-series regression and not exceeding 2500 words including tables and equations.
The optional modules listed on the website for this programme may unfortunately occasionally be subject to change. As you will appreciate key members of staff may leave the University and this necessitates a review of the modules that are offered. Where the module is no longer available we will let you know as soon as we can and help you make other choices.