MSc
Statistics and Management Science

Female student

About this course

  • Entry year: 2012/13
  • Course code: G42A12
  • Applications: University
  • Level: Postgraduate
  • Department: Engineering, Design and Mathematics
  • Campus: Frenchay
  • Duration: One year full-time, lectures and tutorials normally take place on two days each week. We regret we are unable to offer this course part time.
  • Delivery: Full-time
  • Study Abroad: No
  • Programme leader: Richard Lawton

Introduction

There is always demand for well-qualified statisticians and management scientists in a wide range of industries and businesses, as well as government. Why? Because organisations need greater and deeper understanding of statistical and management science methodologies in order to analyse, interpret and extract value from the ever larger amounts of data provided by modern information technology.

This course aims to meet this need through both academic study and the development of applied analytical and modelling skills, mainly computer based. You will also learn the skill of communicating complicated statistical findings to 'non-technical' decision makers. The course equips people from a broad variety of academic backgrounds and professional experience with the knowledge and skills to apply statistical and operational research approaches to a huge range of practical situations. It demonstrates the wide applicability of these approaches within a business or industrial context.

In terms of preparation for a general management career, there are few better ways of gaining an overview and understanding of how organisations work. Typically, statisticians and management scientists are involved in projects which draw on a wide range of business skills and dealings with anyone from the shop-floor and front line, right up to boardroom level. In many organisations, such professionals are a prime source for recruitment into higher levels of general management.

Student's view

"I came to UWE to improve my statistical knowledge and to gain a deeper understanding of different modelling techniques. All these requirements were met thanks to UWE's skilled staff; perhaps some of the best lecturers I have ever met!"
Olivier

Structure

Content

Based on an assessment of your individual needs, there may be some preparatory learning consisting of:

  • independent directed reading on Statistics with structured guidance
  • three days of classes on the Statistics software SPSS and Excel Solver during the two weeks prior to the start of normal classes

The following modules and topics will be covered during the first and second semesters:

  • Applications of Statistics
  • Decision Modelling
  • Business Research Methods
  • Statistical Models
  • Operations Simulations and Forecasting
  • Research Methods
  • Option Module - either Applied Multivariate Techniques or Logistics Optimisation

Normally during the second semester you will start working on your dissertation. This is a substantial piece of independent work accounting for a third of the overall MSc. Most students will normally complete this after completion of the taught part of the course and many take an additional 4 - 6 months to do so.

Please note: The content of the programme may change from year to year, so you might find some variation between that shown here and the final version of your course.

Please see our website for further details on this course, including in depth information on the core and option modules currently available.

Teaching and learning

An essential objective of this programme is that you will be expected to take major responsibility for your own learning through a high proportion of time spent on independent study.

Additionally, lectures, seminars, discussions, case studies and group work will be used to develop the topics covered in the modules and to allow for application of methods to particular problems. There will be extensive use of computer packages to assist analysis. Students come from a wide variety of industrial and commercial backgrounds and will be encouraged to present, discuss and evaluate techniques in light of their own perspectives and experiences, complementing the examples and experiences brought by the lecturers.

A variety of assessment methods will be used depending on the aims of the individual modules. Commonly, this consists of one piece of coursework and a written or oral examination. Extra help in mathematics and statistics is also available through our Mathematics and Statistics Resource Centre.

The 60 credit dissertation will be guided and supported by a personal supervisor.

Study time

You can expect to attend the University two days a week. You should also expect to devote a similar amount of time each week (on average) to independent reading, study and project work.

Assessment

A variety of assessment methods will be used depending on the aims of the individual modules. Commonly this consists of one piece of coursework and a written or oral examination per module.

Special Features

Study facilities

We host our own servers to provide Windows, Linux and Unix based operating systems. There are over 500 available workstations in our teaching laboratories, as well as a large open-access laboratory, providing PC and Unix based machines. We have our own IT Helpdesk, staffed by students from within the department, and available for both students and staff to use. There are also 24 hour computer labs on campus available for student use.

We operate an extensive pastoral care system that includes induction programmes and access to academic staff and student advisers for guidance and support throughout your time here as a student.

Careers/further study

There is an increasing demand in business and industry for graduates with skills in quantitative analysis. One of the reasons for this demand is that there is a need for a greater and deeper understanding of statistical and management science techniques in today's organisations, where information technology is providing ever-increasing amounts of data to be processed, interpreted and exploited. This programme caters for this demand, and will enhance the career prospects of those who successfully complete the course.

In terms of preparation for a general management career, there are few better ways of gaining an overview and understanding of how organisations work. Typically, statisticians and management scientists are involved in projects which draw on a wide range of business skills and dealings with anyone from the shop-floor and front line, right up to boardroom level. In many organisations, such professionals are a prime source for recruitment into higher levels of general management.

Entry

Entry requirements

General requirements

You should have a quantitative background and be a good communicator. Although not a requirement for entry, some previous exposure to statistics and/or management science would be useful.

We welcome applicants without conventional entry requirements but who have substantial relevant work or other experience and who have the motivation and skills to succeed on the course.

International applicants (non UK and EU) should aim to apply by the end of June to allow time to arrange accommodation, finance and any visas.

English Language requirements

Please visit our website for information on English language requirements

Education and work experience

Typically, students enter the programme with a degree which has a significant quantitative content (though not necessarily with a statistical or management science focus). We would normally expect an honours degree at 2.2 or better. Alternatively, you may have a lower classification degree but with two or more years of appropriate experience; or have none of the qualification given above but have substantial work experience and a keen interest in developing your analytical skills. In both these cases it is likely that we would invite you for an informal interview.

Fees

Please contact the department for information on fees payable and payment options or visit our money matters page.

For further information

Page last updated 14 December 2011

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