Postgraduate Courses in the
School of Computing Sciences

MSc Management Science

Introduction

The MSc Management Science at De Montfort University is a taught conversion course with both full-time and part-time students. Full-time, the course lasts for twelve months whilst if taken part-time, the course can last either two or four years, depending on the number of modules taken each year.

Aims and Objectives

The primary aim of the course is to give students a sound understanding of the management science topics that have been found useful when considering a variety of problems in industry and commerce.

The course provides students with analytical skills and an intellectual training which will equip them for a wide range of positions where the ability to think clearly in a problem solving manner is required. We are confident that students graduating from this course will have a broad range of employment opportunities, as well as being prepared for further study in Management Science or associated subjects. For example, it may be possible for some graduates to go on and register for a PhD degree on the basis of their MSc.

What is Management Science?

The term 'Management Science' broadly covers the application of quantitative and analytical skills to the analysis of problems in industry, commerce and government, with this application frequently occurring within a computing environment. However, the effectiveness of this approach is crucially dependent on the co-operation of the people concerned, so in addition to having good technical skills a management scientist also needs to be able to communicate in language that people understand.

Entry Requirements

The normal entry requirement for the MSc course is a good honours degree in a subject with a reasonable quantitative content such as Mathematics, Computer Science, Engineering, Science, Economics and Business Studies. In some circumstances options previously taken by a student would be a deciding factor, while in other circumstances combinations of other qualifications and practical experience may be regarded as equivalent.

The necessary level of mathematics/statistics is covered by most degree courses in the subjects mentioned and some basic computing experience is also desirable. However, we have prepared an induction unit for students to work through prior to starting the taught course. This unit covers the essential elements of mathematics, statistics and computing.

Above all, prospective students must me capable of the breadth of approach appropriate to the multidisciplinary nature of the course.

Course Structure

The course will normally be undertaken in one of the following formats:

One-year full time;

Two-years part-time (taking fourmodules per year);

Four-years part-time (taking two modules per year).

The course comprises eight modules, a project skills unit together with a project. The eight modules are as follows:

Semester 1

• Programming
• Statistical Methods in Industry and Commerce
• OR Modelling
• Finance Reporting

Semester 2

• Simulation
• Forecasting
• Information Systems
• Managing People in Organisations

Students are additionally expected to attend seminars given by invited speakers.

Course Syllabus

• Induction Unit
  This unit provides students with review material in mathematics, statistics and computing. It summarises those aspects of these subjects that students will be expected to know when enrolling on the course. It is not a teaching package, but simply an aid in reviewing relevant material. A detailed set of references is provided to assist students in studying topics they may not have previously covered in sufficient detail. The following areas are covered:
  • Linear and Non-Linear Equations
  • Determinants and Matrices
  • Differentiation and Partial Differentiation
  • Elements of Integration
  • Probability & Probability Distributions
  • One and Two Sample Confidence Intervals and Significant Tests
  • One-Way Analysis of Variance
  • Linear Regression and Correlation
  • Goodness of Fit Tests
  • Using a Wordprocessor and Spreadsheet

• Programming
  This module enables students to understand how a computer works and to have a sufficient grasp of at least one high level programming language so that they can write well structured programs to solve typical problems that occur in a business or OR environment. The following areas are covered:
  • Basic Theory
  • Data and File Structures
  • Study of a Programming Language

• Statistical Methods in Industry & Commerce
  A large number of industrial and commercial problems can be successfully tackled by the application of statistical methods and techniques. Frequently, these techniques form part of computerised systems that control manufacturing or commercial processes. This module develops a number of these methods and techniques, some of which provide a useful background to the Simulation and Forecasting modules. The following areas are covered:
  • Multiple Regression
  • Design and analysis of experiments
  • Design and analysis of sample surveys
  • Quality control and reliability
  • Non-parametric statistical tests

• OR Modelling
  This module covers topics that will develop students' abilities to formulate, solve and interpret the solutions of a range of quantitative models that can be applied in a business context. The primary emphasis of the module will be on the formulation/interpretation aspects rather than on the mathematical details of solution processes. The following areas are covered:
  • Linear and Integer Programming Models
  • Network and Critical Path Models
  • Non-linear Optimisation
  • Dynamic Programming
  • Financial Mathematics and Investment Appraisal

• Financial Reporting
  This module develops an awareness of the financial accounting structure and processes for organisations, an understanding of the organisational role of accounting and a critical perspective of published accounting information. It also considers the broad issues impacting upon published accounting information. The following areas are covered:
  • Accounting, organisations and systems
  • Purposes and processes of constructing financial statements
  • Adaptations and alternatives to the traditional financial accounting model
  • Developments in the reporting function

• Simulation
  This module equips students with the skills necessary to identify and analyse problems, that are amenable to a discrete-event simulation approach, using a simulation language that includes graphical simulation. The following areas are covered:
  • Introduction to systems and the different modelling approaches
  • Elements of number theory, random number generation and associated tests
  • Modelling using a Discrete-Event Simulation Language (e.g. SIMAN)
  • Animating the Simulation Model (e.g. SIMAN/CINEMA)
  • Simulation in Practice

• Forecasting
  This module provides students with a working knowledge and appreciation of forecasting, with a special emphasis on the problem-solving techniques used by industry and commerce. The topics covered are:
  • Time Series Section
    Introduction to time series
    Brief review of classical methods of analysis
    Box-Jenkins methods
    Advanced topics

  • Neural Networks Section
    Introduction to neural networks
    Supervised and unsupervised learning
    An investigation of other algorithms
    Use of a suitable package (e.g.SNNS)

• Information Systems
  This module provides students with a working knowledge of data analysis techniques and gives them an insight into current developments in database systems. It makes use of the advanced database tools currently available in industry. The topics covered are:
  • Relational database management systems, architecture and 4GL facilities. The conceptual database and reality modelling
  • The reality invariants, invariant stability and reality tracking
  • Distributed Database concepts, architecture and schema design
  • Multimedia database technology, storage and retrieval
  • Introduction to the object orientated paradigm

• Managing People in Organisations
  This module creates an awareness of the nature and significance of the behaviour of individuals and groups in organisations. It introduces the major theories of organisational behaviour and identifies emerging issues of organisational behaviour. The topics covered are:
  • Perception
  • Attitudes
  • Learning
  • Motivation
  • Leadership and management styles
  • Organisational structure, culture and change
  • Staff recruitment, selection and appraisal

• Project Skills Unit
  This unit provides guidance in good practice when undertaking a project, and experience in presenting findings and ideas. It should enable the student to effectively manage their project, and to present their findings and work in a cogent manner. It should also help them identify and define a suitable project. The topics covered are:
  • Personal Time Management
  • Project Management
  • Project Selection
  • Written and Verbal Communication
  • Giving Demonstrations

• Project
  The project provides the student with the opportunity to develop and to demonstrate the skills acquired from the taught course in the solution of a practical problem, subject to reasonable commercial or organisational constraints. It also allows the student to experience the role of a consultant in a relatively safe environment, and thus appreciate the problems, pressures and satisfaction that such a job can generate.

Further Information

Assessment
Assessment is by three modes: Coursework, examination and project

For the award of MSc in Management Science a student is required to pass the project and all taught modules.

For the award of MSc with Distinction a student must have passed all taught modules and the project with a grade 'A' in the project and normally grades 'A' or 'B' for the taught modules, of which at least four must be of grade 'A'.

For the award of Postgraduate Diploma a student must have passed either 8 taught modules or the project and at least four taught modules.