2008/09 Undergraduate Module Catalogue
LUBS2195 Introductory Modelling for Management (II)
10 creditsClass Size: 150
Module manager: Dr Luisa Huatucco
Email: lh2@lubs.leeds.ac.uk
Taught: Semester 1 (Sep to Jan) View Timetable
Year running 2008/09
Pre-requisite qualifications
Pass in GCSE Mathematics at grade B or above.This module is mutually exclusive with
| LUBS1195 | Introductory Modelling for Management (1) |
| LUBS1240 | Mathematics and Statistics for Business and Economics 1 |
| MATH0111 | Elementary Differential Calculus (Version 1) |
| MATH0131 | Elementary Differential Calculus (Version 3) |
| MATH0380 | Foundation Applied Mathematics for Business |
| MATH1050 | Calculus and Mathematical Analysis |
| MATH1150 | Mathematics for Geophysical Sciences 2 |
| MATH1331 | Linear Algebra with Applications |
| MATH1460 | Mathematics for Geophysical Sciences 1 |
| MATH1932 | Calculus, ODEs and Several-Variable Calculus |
| MATH1960 | Calculus |
| MATH1970 | Differential Equations |
| MATH2375 | Linear Differential Equations and Transforms |
| MATH2640 | Introduction to Optimisation |
| MATH2790 | Modelling and Simulation |
| MATH3171 | Algebra and Numbers |
| MATH3473 | Numerical Solutions of Partial Differential Equations |
| MATH3474 | Numerical Methods |
| MATH3715 | Linear Models |
| MATH3743 | Design and Analysis of Experiments |
| MATH3772 | Multivariate Analysis |
This module is not approved as an Elective
Objectives
On completion of this module, students should be able to:Appraise the value of basic modelling techniques to a wide range of business situations and business problems; and demonstrate the transferable skills of numeracy and quantitative analysis.
Learning outcomes
On completion of this module, students should be able to:
- Solve business problems using the business modelling techniques taught in the module.
- Evaluate different alternatives in a business context.
- Analyse numerical data and derive managerial recommendations.
Syllabus
Introduction to the most commonly used types of business models comprising: Project planning (Critical Path Analysis); Scheduling (Gantt charts, sequencing rules, rescheduling); Decision analysis (decision rules, decision trees); Simulation (queues, simulation tables, random inputs, output interpretation); Financial analysis (index numbers, interests, present values, series of payments); Linear programming (LP models, graphical and analytical solutions; sensitivity analysis); Optimisation (profit maximisation) and Forecasting (time series, trends and seasonal effects).
Teaching methods
| Delivery type | Number | Length hours | Student hours |
| Lecture | 11 | 2.00 | 22.00 |
| Seminar | 8 | 1.00 | 8.00 |
| Private study hours | 70.00 | ||
| Total Contact hours | 30.00 | ||
| Total hours (100hr per 10 credits) | 100.00 | ||
Opportunities for Formative Feedback
Weekly assessments will be collected from the class and some will be marked and returned.Methods of assessment
Exams
| Exam type | Exam duration | % of formal assessment |
| Standard exam (closed essays, MCQs etc) | 2 hr 00 mins | 100.00 |
| Total percentage (Assessment Exams) | 100.00 | |
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
Reading list
The reading list is available from the Library websiteLast updated: 09/02/2009
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- Undergraduate module catalogue
- Taught Postgraduate module catalogue
- Undergraduate programme catalogue
- Taught Postgraduate programme catalogue
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