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2012/13 Undergraduate Module Catalogue
LUBS2195 Introductory Modelling for Management (II)
10 creditsClass Size: 150
Module manager: Dr Luisa Huatuco
Email: lh2@lubs.leeds.ac.uk
Taught: Semester 1 (Sep to Jan) View Timetable
Year running 2012/13
Pre-requisite qualifications
Pass in GCSE Mathematics at grade A or above.This module is mutually exclusive with
LUBS1195 | Introductory Modelling for Management (1) |
LUBS1240 | Maths&Stats For Bus&Ec 1 |
MATH0111 | Elementary Diff Calculus 1 |
MATH0131 | Elementary Differential Calculus (Version 2) |
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 | Lin Dif Equations & 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) and
- Optimisation (profit maximisation).
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: 22/04/2013
Browse Other Catalogues
- Undergraduate module catalogue
- Taught Postgraduate module catalogue
- Undergraduate programme catalogue
- Taught Postgraduate programme catalogue
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