Module Information

Module Identifier
Module Title
Data Analysis and Quantitative Techniques
Academic Year
Intended for use in future years

Course Delivery

Delivery Type Delivery length / details
Lecture 36 Hours.
Practical 10 Hours.


Assessment Type Assessment length / details Proportion
Semester Assessment 3,000 word essay: discussion of the applicability of different methodological approaches to the students research project - 80% 2,000 word critical review and/or application of a quantitative methodology covered within the module - 20%  100%

Learning Outcomes

On successful completion of this module students should be able to:

* Demonstrate competency in understanding and applying a range of research methods, to enable the collection of both quantitative and qualitative data.

* Display knowledge of the management of research data, and the use of IT in such data management

* Demonstrate skills in conducting research in a manner which is consistent with professional practice

* Demonstrate an awareness of the key skills involved in analysing quantitative and qualitative data.

* Demonstrate an awareness of a range of quantitative techniques and related software.

* Demonstrate an appreciation of relevant applications of quantitative methodologies


This module aims to provide students with a broad knowledge of a range of methodological and analytical skills, which they can apply in a variety of research contexts. The module is aimed at students who have no previous experience with qualitative analysis, but who have previously studied basic quantitative techniques such as regression analysis. The module complements the coverage of quantitative methods offered in PGM0620 (Empirical Methods).

Brief description

The module firstly offers students a foundation in the basic principles of qualitative research methodology. It will provide students with an introduction to the major methods of qualitative data collection and analysis, explain how qualitative data are actively constructed and interpreted by the reseracher, and offer an appreciations of the practical and epistemological concerns raised by qualitative data collection. This will include a consideration of questionnaire design, interviewing techniques, survey design and qualitative data analysis. This will be complemented by coverage of econometric methodologies which can be applied in the context of PhD study in the social sciences. This will include advanced time series analysis, event study methodology and performance measurement. Practical sessions will provide insights to the application of the techniques, including the use of relevant software.


Part A: Data collection and Qualitative analysis
Bridging the Quantitative-Qualitative Divide
Combining Methods
Data sources and context
Internet data collection
Sampling Theory
Survey design and intervviewing
Questionnaire design
The nature and use of qualitative data
Archival and documentary analysis
Focus groups
Participant observation
Semi structured interviewing
Using contemporary texts
Content and discourse analysis

Part B: Quantittive techniques
Event study methodology
High frequency data analysis
Efficiency frontier models
Limited dependent variable models
Performance measurement
Vector Augoregression (VAR) Analysis and the Johansen ML Procedure
Autoregressive Distributed Lag Models - Cointegration

Reading List

Recommended Text
Brooks, Chris (2002) Introductory Econometrics for Finance Cambridge University Press Primo search Bryman, Alan (2004) Social Research Methods Oxford, Oxford University Press Primo search Burns, Robert B (2000) Introduction to Research Methods London, Sage Primo search Flick, Uwe (2002) An Introduction to Qualitative Research London, Sage Primo search Mason, Jennifer (2002) Qualitative Researching London, Sage Primo search Ryan B, Scapens R W and Theobald M (2002) Research Method and Methodology in Accounting and Finance 2nd edition Thomson Primo search de Vaus, David (2001) Surveys in Social Research London, Routledge Primo search


This module is at CQFW Level 7