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 data analysis tools and techniques and data sources used to solve problems in a business and management environment. The module focuses on how to use Excel to perform data analysis and how to interpret the resulting analyses 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 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:
Excel functions and tools for data analysis
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
Introduction to sampling
Hypothesis test for a mean
Simple Linear Regression Analysis
Students should be able to demonstrate knowledge and understanding of:
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
9. Use Excel for data analysis and presentation.
Teaching will be delivered through a combination of synchronous and asynchronous sessions including lectures, tutorials, drop-in sessions, discussion boards and other online learning opportunities.
MCQ 20%, Test 20%, Coursework report 60% (approx 1500 words)
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.