Quantitative Methods 2A

Code

BUSI2055

School

Nottingham University Business School

Level

2

Credits

10

Semesters

Autumn Malaysia

Summary

Further maths and statistics including topics such as linear algebra, constrained optimisation, difference equations and hypothesis testing.

Target Students

Available to Part I and Part II students who have the required pre-requisite BUSI1039 Quantitative Methods 1b. CANNOT be taken by students from the Schools of Economics or Mathematical Sciences.

Classes

• One 1-hour workshop each week for 4 weeks
• One 2-hour lecture each week for 5 weeks
• One 2-hour lecture each week for 6 weeks

Assessment

• 20% Coursework 1: Workshop Exercises
• 80% Exam 1 (1-hour-30-minute): One 1.5-hour examination

Assessed by end of autumn semester

Educational Aims

Learning Outcomes

Knowledge and understanding

This module develops a knowledge and understanding of:

• Relevant quantitative techniques, including mathematical and statistical methods.

Knowledge and understanding (Industrial Economics)

This module develops a knowledge and understanding of:

• Mathematical methods for economics.
• Statistical methods for economics.
• The nature, sources and uses of quantitative data and an ability to select and apply appropriate methods that economists might use to analyse such data.

Intellectual skills

This module develops:

• The ability to analyse and evaluate a range of business data, sources of information and appropriate methodologies, which includes the need for strong digital literacy, and to use that research for evidence-based decision-making.

Professional practical skills

This module develops:

• Numeracy and quantitative skills to manipulate data, evaluate, estimate and model business problems, functions and phenomena.
• Facility with key concepts used in decision making, including equilibrium, expectations and marginal analysis.

Transferable (key) skills

This module develops:

• Articulating and effectively explaining information.
• Subject-specific transferable skills including abstraction, analysis, and problem framing.

Conveners

• Dr Hsin Vonn Yvonne Seow
• Dr Tan Chee Meng