# Unit information: Quantitative Analysis in Management in 2018/19

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Unit name Quantitative Analysis in Management EFIM10014 20 C/4 Teaching Block 1 (weeks 1 - 12) Dr. Holland Not open None None School of Management Faculty of Social Sciences and Law

## Description

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:
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

## Intended learning outcomes

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

## Teaching details

Weekly lectures and seminars/computer-based workshops.

## Assessment Details

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)