Data Analysis for Management
ECTS: 8 credits
Course Co-ordinator: Chris Kirkbride
Lecturer and Contact Details
Chris Kirkbride (A69a, Dept. of Management Science x93296, email@example.com)
Pre-requisites: MSCI100 or 110, or equivalent
Term taught: Michaelmas
This course is not available to students who have taken as a Part I subject either MATH 100 or MATH 110 or MATH 140 or MSCI 101. It is not available to students who are taking MATH 230 and MATH 235 or MNGT 212.
The purpose of this course is to provide students with an introduction to statistical techniques and their applications in the context of business and management problems. In addition, the course is designed to develop students' abilities to make effective use of computer software for data analysis.
Subject Specific Learning Outcomes:
Students who successfully complete the course will be able to
- understand key concepts for quantifying and managing uncertainty and random variations in business and management problems;
- perform computer-aided data analysis using EXCEL; and
- analyse data skilfully.
- The course should help to develop decision making and analytical skills.
Outline Course Plan
Lecture times: Friday 11.00 – 12.00 and 13.00 - 14.00 George Fox LT1
The course covers the following topics:
- Descriptive Statistics
- Probability Distributions
- Hypothesis Testing
- Regression Analysis
The course consists of two hours of lectures and one hour of seminars or workshops per week. Seminars will run in weeks 2, 3, 4, 6, 8 and 10.
Computing workshops, using EXCEL, will run in Weeks 5, 7 and 9.
Attendance at seminars and workshops is compulsory for all students on the course.
Assignment to seminar and workshop groups is automatic and should be added to your timetable. Note that your assigned seminar and workshop will be in a different time slot in the week they occur.
Lectures will be used to explain the material and attendance is extremely important. Seminar and workshop exercises will be posted on the webboard at regular intervals through the course. An essential part of learning quantitative techniques is to practice answering questions. You cannot expect to do well in this course without spending time solving exercises on your own. It is therefore very important that you attempt the seminar and workshop exercises before the session. The purpose of attending these sessions is to discuss the exercises and/or aspects of the lectures with which students have found difficulties. Furthermore, solutions to the exercises will be posted on the webboard.
Many people find maths difficult. You may well find that at certain times during this course you cannot follow some of the arguments in terms of the strategy and/or the detailed calculations. At these times persevere and seek help via office hours. The chances are that it will all fall into place in time, provided that you carry on working on it. Although the material on this course isn't easy, once you've mastered it - and you can master it, the rewards are high, both in terms of course marks and vocational relevance. Have fun and enjoy the course.
All lecture slides, seminar/workshop questions and seminar/workshop solutions will be posted on the webboard at regular intervals through the course. You will be notified in lectures of updates to the webboard - otherwise just check it regularly.
If you have problems printing material (which will be in Word and pdf formats) please contact Fran Riley (ext 92726, firstname.lastname@example.org) in the Undergraduate Office (A13).
You may require this and other course papers to support an application for exemptions from examinations of professional bodies. The department may not be able to supply copies of this course paper at a future date, so keep it safe.
Please note that the principal ways for us to get in touch with students concerning administrative matters will be via Moodle and university e-mail.
Please make sure that you check Moodle and your University e-mail regularly.
There will be 2 coursework assessments and a summer examination. The first coursework is a test in Week 8. The second coursework is an individual project in which you will carry out a data analysis exercise in Excel and write a report. The test and the examination will be open book format. The test will be 50 minutes in duration. The examination will consist of one paper of two hours and 15 mins in duration. The coursework assessments comprise one-third of your final mark, the examination two-thirds. The contribution to your final mark from the individual pieces of work are as follows:
Coursework Test 1 15%
Coursework Project 15%
Final exam 70%
A course text has been recommended for this course:
Louise Swift and Sally Piff (2010), Quantitative Methods for Business, Management & Finance (3rd Edition), Palgrave.
This text covers the material taught in this course and provides a useful reference for study in your own time with exercises that support the topics covered in the lectures.
Many texts have been written on introductory statistics and probability used within a business context. I do recommend that students, especially those who are struggling with some of the concepts and material, read around the subject. Different information sources may approach the material from a slightly different perspective which may aid your understanding. There are a number of very helpful textbooks which contain additional details and examples of the topics we cover in this course and have been previously used in similar courses:
Paul Newbold, William Carlson, and Betty Thorne (2010), Statistics for Business and Economics (7th edition), Pearson.
Alan H. Kvanli, C. Stephen Guynes and Robert J. Pavur (2003), Introduction to Business Statistics: A Computer Integrated Approach (6th edition), Thomson.
Anderson, Sweeney, Williams, Freeman and Shoesmith (2010), Statistics for Business and Economics (2nd Edition), Thomson.
D.M. Levine, M.L. Berenson, and D. Stepjam (2008), Statistics for Managers using Microsoft Excel (5th edition). Prentice Hall.
Robert Stine and Dean Foster (2010), Statistics for Business: Decision Making and Analysis, Pearson. (Note: used as MNGT212 textbook)