FE7066 - Data Analysis for Global Business (2023/24)
|Module specification||Module approved to run in 2023/24|
|Module title||Data Analysis for Global Business|
|Module level||Masters (07)|
|Credit rating for module||20|
|School||Guildhall School of Business and Law|
|Total study hours||200|
|Running in 2023/24(Please note that module timeslots are subject to change)||
This module offers students a critical understanding of data and different techniques employed for data analysis in relation to the global business.
To provide students with practical skills necessary to undertake data analysis for global business, the aims of the module are:
- to introduce methods for data handling
- to discuss mathematical and statistical foundations for data presentation and analysis
- to develop thorough analysis and synthesis of theory and practice in relation to the subject areas
- to foster a critical awareness and deep interest in global business issues
- to master steps in formulating an econometric model
- to provide an opportunity to students for critical self-reflection, studying and data analysis skills and knowledge.
The module uses Bloomberg for teaching delivery and enables students to join the elite group of Bloomberg users around the world. The module also enables the development of expertise in the use of packages such as SPSS, EViews and NVivo to analyse data.
Note: If there are not sufficient student numbers to make a module viable, the School reserves the right to cancel such a module. If the School cancels a module it will use its reasonable endeavours to provide a suitable alternative.
Prior learning requirements
- Mathematical and statistical foundations for data presentation and analysis
- Primary qualitative data recording, processing and analysis
- Primary quantitative data recording, processing and analysis
- Sources for secondary data collection
- Generalised linear regression models
- Univariate time series modelling and forecasting
- Modelling long-run relationships (cointegration and VARs)
- Panel models
All the econometric and statistical techniques are demonstrated using appropriate econometric and statistical tools and real-world datasets relating to global business.
Balance of independent study and scheduled teaching activity
The module will involve a series of lectures, seminars and practical sessions delivered by the tutor.
These sessions will help the students understand the tools and techniques related to data analysis for global research. Students will also need to use some of the 'directed learning’ allocation of hours for individual preparation of data analysis tasks.
Training sessions in SPSS and EViews [for quantitative data analysis] and Nvivo [qualitative data analysis] will be provided. The software programmes are available to all students at no extra charge.
On successful completion of this module students will be able to:
- understand different types of data and techniques employed in data analysis for the development of theory and empirical research in subject areas related to global business;
- process and analyse primary data in the subject areas;
- investigate the relationship of quantitative data variables in the subject areas;
- appropriately interpret the results from an empirical exercise and develop evidence-based decisions and incorporate technical analysis into a clearly written business-oriented report.
Assessment will consist of students’ writing two pieces of coursework demonstrating their understanding of the tools and techniques of data analysis in relation to global business issues.
The first coursework will comprise a report of 1,000 words. Students will be required to write a formal report on results of analysing primary data for research. This includes relevant elements of data sources, data displaying and analysis.
The second coursework will comprise a report of 2,000 words. A combination of tasks such as investigating relationship of variables, testing of hypotheses and forecasting will be included in the report. This coursework will focus on analysing secondary quantitative data collected from researching global business issues.
The feedback consists of comments addressing various aspects of students’ analytical reports.
Reading List Talis Link:
Bekes, G. and Kezdi, G. (2021) Data Analysis for Business, Economics, and Policy Cambridge University Press, Cambridge.
Saunders, M. N. K., Lewis, P. and Thornhill, A. (2018), Research Methods for Business Students, 8th Edition, Pearson
Wooldridge, J. (2019) Introductory Econometrics: A Modern Approach 7th edition, South-Western College Publishing
Bell, E., Bryman, A. and Harley, B. (2018), Business Research Methods, 5th Edition, Oxford University Press, Oxford
Benningo, S. (2014), Financial modelling,4th Edition, The MIT Press, Cambridge MA
Brooks, C. (2019), Introductory Econometrics for Finance, 4th Edition, Cambridge University Press, Cambridge
Creswell, J. (2014), Research Design: Qualitative, Quantitative, and Mixed Methods Approaches, Sage, London
Denzin, N. and Lincoln, Y. (2017), The SAGE Handbook of Qualitative Research, Sage, London
Dowson, C. (2019), Introduction to Research Methods: a practical guide for anyone undertaking a research project. 5th Edition, Robinson, London
Easterby-Smith, M., Thorpe, R. and Jackson, P. (2018), Management and Business Research, 6th Edition, Sage, London
Evans, J. R. (2017) Business Analytics, Global Edition, Pearson
Ghauri, P. Grønhaug, K. and Strange, R. (2020), Research Methods in Business Studies, 5th Edition, Cambridge University Press, Cambridge
Groebner,D., Shannon, P. and Fry, P. (2017), Business Statistics: a decision-making approach, 10th Edition, Pearson
Koop, G. (2006), Analysis of Financial Data, John Wiley
Myers, M. (2011), Qualitative Research in Business and Management, Sage, London
Patton, M. (2002), Qualitative Research and Evaluation Methods, 3rd Edition, Sage, London
Rubin, H., and Rubin, I. (2005), Qualitative Interviewing, 2nd Edition, Sage, London
Rachev, S. (2007), Financial econometrics: from basics to advanced modeling techniques, Wiley
Wisniewski, M. (2019), Quantitative Analysis for Decision Makers, 7th Edition, Pearson
Other relevant resources:
Qualitative Research in Financial Markets
Electronic data sources such as Bloomberg
EViews 11 User’s Guide (1994–2020) Quantitative Micro Software, LLC, USA
NBS, Network for Business, available online: http://nbs.net/about/what-is-business-sustainability/ and http://nbs.net/knowledge/business-models-for-shared-value/executive-guide/
Software such as SPSS, EViews and NVivo