| Unit name | Quantitative Analysis in Management |
|---|---|
| Unit code | EFIM10014 |
| Credit points | 20 |
| Level of study | C/4 |
| Teaching block(s) |
Teaching Block 1 (weeks 1 - 12) |
| Unit director | Professor. Holland |
| Open unit status | Not open |
| Pre-requisites |
None |
| Co-requisites |
None |
| School/department | School of Management - Business School |
| Faculty | Faculty of Social Sciences and Law |
The aim of this module is to provide students with an understanding of the use of different statistical techniques and data sources used to solve problems in a business and management environment. The module focuses on how to interpret data involving uncertainty and variability; how to model and analyse the relationships within business data; and how to make correct inferences from the data (and recognise incorrect inferences). The module utilises advanced computer modelling tools available in Microsoft Excel and other modelling software packages to analyse and present quantitative data. It therefore develops practical skills in statistical and mathematical techniques commonly used in business and management decision-making. It draws on fundamental quantitative analysis and business statistics theories with contemporary computational skills to critically evaluate complex business problems and to cross-examine them through computer technologies. The module will also prepare students for the reading, comprehension and interpretation of original business and management research articles that are based on quantitative data and statistical analysis.
Indicative course content:
Quantitative Modelling in Business
Algebraic Expressions and Equations (including financial applications)
Introduction to Statistical Variables (types and data collection)
Statistical Summaries (measures of central tendency and dispersion – means, variance and skewness)
Elementary Probability
Correlation and Association
Regression Analysis
Differentiation
Linear Programming
Simultaneous Equations
Students should be able to demonstrate knowledge and understanding of:
1. The role of quantitative analysis in generating value from data
2. The scope and nature of different quantitative techniques
3. The role of probability theory in modelling uncertainty
4. Basic concepts of statistical and mathematical analysis and inference models
Having successfully completed the unit, students will be able to:
5. Apply basic statistical and mathematical techniques to business and management problems
6. Use probability distributions to model uncertainty in real life problems
7. Communicate quantitative ideas effectively both in oral and written form
8. Use a variety of visual models to represent statistical results
Weekly lectures and seminars/computer-based workshops.
A 2-hour written exam (60% in total) will assess both the interpretation of management data and its analysis and the student’s technical skills in statistical analysis. (ILOs 1- 6)
An analysis of a real data set (40% in total). The analysis will provide: a management report (no more than 1000 words) which extracts value and meaning and presented in an appropriate form for a key (generalist) stakeholder. The report will be supported by a technical appendix providing the statistical analysis that supports the conclusions and claims in the management report. (ILOs 5 – 8)
Students will follow a range of standard statistics / quantitative analysis textbooks for business and management, and there is any number of on-line support websites for maths and statistics. The following is indicative of the reading / resources available:
Anderson, D.R., Sweeney, D.J., Wiliams, T.A., Freeman, J and Shoesmith, E. (2017)Statistics for Business and Economics, Andover: Cengage Learning
Moore, D.S., McCabe, G.P. and Craig, B (2014). Introduction to the Practice of Statistics, Houndsmills: Palgrave Macmillan.
Swift, L. and Piff, S. (2014) Quantitative Methods for Business, Management and Finance, Basingstoke: Palgrave Macmillan.
