Module manager: Dr Kausik Chaudhuri
Email: K.Chaudhuri@lubs.leeds.ac.uk
Taught: Semester 2 (Jan to Jun) View Timetable
Year running 2024/25
LUBS1275 Mathematics and Statistics for Economics and Business 1A OR LUBS1285 Mathematics and Statistics for Economics and Business 1B
| MATH0111 | Elementary Diff Calculus 1 |
| MATH0212 | Elementary Integral Calculus (Version 1) |
| MATH0370 | Introduction to Applied Mathematics 2 |
| MATH1050 | Calculus and Mathematical Analysis |
| MATH1331 | Linear Algebra with Applications |
| MATH1400 | Modelling with Differential Equations |
| MATH2600 | Numerical Analysis |
| MATH2640 | Introduction to Optimisation |
| MATH2715 | Statistical Methods |
| MATH2740 | Environmental Statistics |
| MATH3723 | Statistical Theory |
| MATH3772 | Multivariate Analysis |
This module is not approved as a discovery module
This module gives you a platform in advanced mathematical methods as it applies to business. It develops your ability to use the mathematical tools to analyse problems in business and economics. Emphasis is placed in developing ability in translating business/economic problems that students will encounter in their other modules, into mathematical models, and on solving these models.
This module aims to provide students with the mathematical techniques required to solve problems arising in business and economic analysis. The module provides grounding in the theory and application of the Matrix Algebra, Differential Calculus, Unconstrained and Constrained optimisation along with comparative statics widely used in Business and Economics.
Upon completion of this module students will be able to:
- Recognise, select and accurately apply advanced techniques in mathematics
- Identify literature that utilises advance mathematical techniques in accounting and finance, economics and management
Upon completion of this module students will be able to:
Transferable
- Perform with high levels of accuracy
Subject Specific
- Analyse issues and solve problems in accounting & finance, economics and management
- Reason logically and work analytically with abstract concepts
Indicative content:
- Linear Equations
- Multivariate Analysis in Economics
- Finance and Management
- Vector, and Matrix Algebra
- Multivariate Optimisation – Unconstrained and Constrained
- Non-Linear Programming
| Delivery type | Number | Length hours | Student hours |
|---|---|---|---|
| Workshop | 10 | 1 | 10 |
| Lecture | 13 | 1 | 13 |
| Private study hours | 77 | ||
| Total Contact hours | 23 | ||
| Total hours (100hr per 10 credits) | 100 | ||
This could include a variety of activities, such as reading, watching videos, question practice and exam preparation.
Your teaching methods could include a variety of delivery models, such as face-to-face teaching, live webinars, discussion boards and other interactive activities. There will be opportunities for formative feedback throughout the module.
| Exam type | Exam duration | % of formal assessment |
|---|---|---|
| Standard exam (closed essays, MCQs etc) | 2.0 Hrs Mins | 100 |
| Total percentage (Assessment Exams) | 100 | |
The resit for this module will be 100% by 2 hour examination.
The reading list is available from the Library website
Last updated: 4/29/2024
Errors, omissions, failed links etc should be notified to the Catalogue Team