Module overview
Quantitative Methods II builds upon the material learnt in Quantitative Methods I and introduces students to some commonly used statistical methods for analysing data.
Linked modules
Pre-requisites: RESM6004
Aims and Objectives
Learning Outcomes
Learning Outcomes
Having successfully completed this module you will be able to:
- Demonstrate knowledge and understanding of core methods of regression modelling.
- Select appropriate statistical methods in order to answer specific research questions.
- Analyse quantitative data using SPSS.
- Conduct, interpret and report statistical analyses. Critically evaluate the results of such analyses.
Syllabus
The course covers logistic regression and other models for categorical data. Indicative topics include: binary response variables, the linear probability model, probabilities and odds, the logistic regression model, model interpretation, model selection, multinomial logistic regression, models for ordinal data, and log-linear models. The final part of the module covers a short introduction to the data reduction methods of principal component analysis and factor analysis.
Learning and Teaching
Teaching and learning methods
If full face-to-face teaching has not been resumed, teaching will be delivered by a mixture of synchronous and asynchronous online methods, which may include a combination of lectures, tutorials and computer workshops. A range of resources will also be provided for further self-directed study. Face-to-face teaching opportunities will be explored depending on circumstances and feasibility.
| Type | Hours |
|---|---|
| Independent Study | 80 |
| Teaching | 20 |
| Total study time | 100 |
Resources & Reading list
General Resources
Software requirements. You will require access to SPSS, which is available on the University’s computer workstations and can be downloaded to your own computer for use with your studies.
Textbooks
Hosmer, D. W. and Lemeshow, S. (2000). Applied Logistic Regression. Wiley.
Agresti, A. (2007). An Introduction to Categorical Data Analysis. New York: Wiley.
Manly, B. F. J. (2005). Multivariate Statistical Methods: a Primer. Chapman and Hall/CRC.
Field, A. (2009). Discovering Statistics Using SPSS. London: Sage.
Assessment
Assessment strategy
The module will be assessed through coursework.
Summative
This is how we’ll formally assess what you have learned in this module.
| Method | Percentage contribution |
|---|---|
| Coursework assignment(s) | 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