BSc Management with Industrial/Professional Experience

Year of entry: 2024

Course unit details:
Quantitative Methods for Business and Management

Course unit fact file
Unit code BMAN10960
Credit rating 20
Unit level Level 1
Teaching period(s) Full year
Available as a free choice unit? No


Semester 1:

  • Data collection and sampling
  • Presenting and grouping data
  • Summarising data
  • Set notation and probability
  • Index numbers
  • Compound interest and growth
  • Discounting and reduced balance depreciation
  • Savings endowments and sinking funds
  • Loans, mortgages, and annuities
  • Investment decisions (e.g., NPV, IRR)


Semester 2:

  • Modelling relationships and linear functions
  • Least squares regression
  • Quadratic and polynomial functions
  • Hyperbolic and exponential functions
  • Multivariate functions and an introduction to analysis
  • An introduction to time series
  • An introduction to forecasting
  • An introduction to decision analysis
  • An introduction to linear programming

The material will follow the course text closely. Lectures will be supported by materials, including spreadsheets, on Blackboard.


This course is core for first year students on BSc Management / Management (specialism), BSc International Management, BSc International Management with American Business Studies.

Pre-requisites: N/A
Co-requisites: None
Dependent courses:
•    BMAN24621 Business Data Analytics
•    BMAN31152 Decision Analysis for Business & Management

Programme Restrictions: This course is core for first year students on BSc Management / Management (specialism), BSc International Management, BSc International Management with American Business Studies.


To introduce students to the fundamental principles, problem areas, and techniques of Quantitative Methods for Business and Management. Students will be taught the basic concepts of modelling and analysis for supporting decision making. Concepts are introduced through examples of applications. Tools used include basic algebra, graphing and spreadsheet software.


Learning outcomes

At the end of the course students should be able to:

  • Apply basic mathematical operations and perform basic algebra
  • Appreciate the use of scientific methodology in Management
  • Understand issues in the collection and analysis of quantitative data for supporting management decision making
  • Understand and apply a range of basic statistical methods
  • Understand and apply basic techniques used in the mathematics of finance
  • Recognise patterns in data
  • Appreciate the value and limitations of using quantitative models for supporting decisions
  • Develop and analyse functions to provide information to decision makers
  • Apply basic models to problems and data sets, analyse these models and provide information to decision makers
  • Use spreadsheet tools to display and analyse data and models.


Teaching and learning methods

Methods of delivery:
•    Lectures: 30hrs
  o    1hr per week over 10 weeks in Semester 1
  o    2hrs per week over 10 weeks in Semester 2
•    Case lectures: 9hrs
  o    2hrs over 3 times in Semester 1
  o    1hr over 3 times in Semester 2
•    (Optional) Drop-in math surgeries: 10hrs
  o    1hr over 5 times in Semester 1
  o    1hr over 5 times in Semester 2
•    Private study: 151hrs
•    Total study hours: 200hrs split between lectures, self-study and preparation for classes, case-studies


Employability skills

We believe the following transferable skills are exercised in this module: Analytical skills Decision making IT skills Numeracy skills Problem solving Research

Assessment methods

4 individual open-book online (Blackboard) exams (i.e., 2 each Semester) based on the lectures, exercises and case lectures

•    Semester 1: 50% main exam
•    Semester 2: 50% main exam

Each semester, three collections of problem sets (i.e., cases) will be made available to the students, who will have to work on them individually. The resolution of these cases will be discussed in the case lecture hours. The assessment will be in the form of open-book problem solving exercises which will go further in the case problem sets and require a range of techniques learnt in the course to be applied. The assessment will be online exams which will ask questions similar and related to the ones solved in the case lectures.

Feedback methods

  • Informal advice and discussions during lectures, case  lectures and math surgeries
  • Formative self-tests available in Blackboard
  • Responses to student emails and feedback provided via the online discussion forum.
  • Generic feedback posted on Blackboard regarding overall examination performance.

Recommended reading

CORE Text (required)

  • Dewhurst, F. (2006), Quantitative Methods for Business and Management, (2nd Edition), McGraw-Hill

Other Texts (Available in libraries)

  • D. Waters (1997 or later ),Quantitative Methods for Business, Addison-Wesley
  • C. Morris (2000 or later), Quantitative Approaches in Business Studies, Pitman.
  • J. Curwin & R. Slater (1999), Quantitative Methods for Business Decisions, Thomson Business Press
  • L. Swift (1997 or later ), Mathematics and Statistics for Business, Management and Finance, Macmillan
  • M. Wisniewski (1996), Foundation Quantitative Methods for Business, Pitman
  • I. Jacques (1995), Mathematics for Economics & Business, Addison Wesley
  • A. Mizrahi & M. Sullivan (1990), Mathematics for Business & Social Sciences: An applied approach, John Wiley


Study hours

Scheduled activity hours
Lectures 39
Seminars 12
Independent study hours
Independent study 149

Teaching staff

Staff member Role
Panagiotis Sarantopoulos Unit coordinator
Xian Yang Unit coordinator
Fanlin Meng Unit coordinator

Additional notes

For Academic Year 2024/25

Updated: March 2024

Approved by: March UG Committee

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