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This is an introductory course on the fundamental principles, problem areas and techniques of Quantitative Methods for Business and Management. The course covers the basic concepts of statistics and financial mathematics (Semester 1), modelling and analysis for supporting decision making (Semester 2). The main concepts are introduced through examples of applications. Tools used include basic algebra, graphing and MS Excel. Although the course is essentially mathematical in nature, a rigid mathematical treatment is avoided; the necessary mathematical concepts are derived from examples rather than through proofs. 

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.
 

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.

 

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.

 

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 

Semester 1:

- Lectures: 10 hours  

   -- 10 x 1 hours face-to-face

- Case Lectures: 6 hours  

   -- 3 x 2 hours face-to-face

- Maths Surgeries: 5 hours (these are optional sessions)

   -- 5 x 1 hours face-to-face

Semester 2:

- Lectures: 20 hours  

   -- 10 x 2 hours face-to-face

- Case Lectures: 3 hours  

   -- 3 x 1 hours face-to-face

- Maths Surgeries: 5 hours (these are optional sessions)

   -- 5 x 1 hours face-to-face

Private study: 151 hours

Total study hours: 200 hours split between lectures, self-study and preparation for classes, case-studies

Weekly online asynchronous quizzes provide opportunities for formative feedback and re-enforce understanding of the course content. 

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

Appreciate the use of scientific methodology in Management

Apply basic mathematical operations and perform basic algebra

Recognise patterns in data

Appreciate the value and limitations of using quantitative models for supporting decisions 

Use spreadsheet tools to display and analyse data and models 

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 

Final exam (one per semester) 100% (50% per semester)
 

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

CORE Text: Les Oakshott (2020),Essential Quantitative Methods, Bloomsbury