2023/24 Undergraduate Module Catalogue
LUBS1285 Mathematics and Statistics for Economics and Business 1B
10 creditsClass Size: 740
Module manager: Henry Duncanson
Email: H.Duncanson@leeds.ac.uk
Taught: Semester 2 (Jan to Jun) View Timetable
Year running 2023/24
Pre-requisite qualifications
LUBS1275 Mathematics and Statistics for Economics and Business 1AOR
A-level Maths Grade B
This module is mutually exclusive with
LUBS1630 | Introductory Statistics for Business |
MATH0212 | Elementary Integral Calculus (Version 1) |
MATH1050 | Calculus and Mathematical Analysis |
MATH1400 | Modelling with Differential Equations |
MATH1710 | Probability and Statistics I |
This module is not approved as a discovery module
Module summary
This module aims to provide students with a basic knowledge of mathematics and statistical tools that are required to understand economics and business. It is intended to provide both reinforcement of learning from A-level mathematics or LUBS1275 Mathematics and Statistics for Economics and Business 1A and to introduce new mathematical and statistical tools to students.Objectives
This module aims to provide students with a basic knowledge of mathematics and statistical tools that are required to understand economics and business. It is intended to provide both reinforcement of learning from A-level mathematics or LUBS1275 Mathematics and Statistics for Economics and Business 1A and to introduce new mathematical and statistical tools for students.Learning outcomes
Upon completion of this module students will be able to:
- further understand the fundamental techniques of mathematics and statistics associated with economics and business
- use and apply the techniques to economics and business examples
Skills outcomes
Upon completion of this module students will be able to:
Transferable
- apply logic to solve problems
Subject specific
- utilise mathematics and statistics as tools to solve problems in economics and business
Syllabus
Indicative content:
Probability distributions; sampling, intervals and hypothesis testing; regression; integration and partial differentiation; and optimisation.
Teaching methods
Delivery type | Number | Length hours | Student hours |
Workshop | 11 | 2.00 | 22.00 |
e-Lecture | 11 | 1.00 | 11.00 |
Private study hours | 67.00 | ||
Total Contact hours | 33.00 | ||
Total hours (100hr per 10 credits) | 100.00 |
Private study
This could include a variety of activities, such as reading, watching videos, question practice and exam preparation.Opportunities for Formative Feedback
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.Methods of assessment
Exams
Exam type | Exam duration | % of formal assessment |
Standard exam (closed essays, MCQs etc) | 2 hr | 100.00 |
Total percentage (Assessment Exams) | 100.00 |
The resit for this module will be 100% by 2 hour examination.
Reading list
The reading list is available from the Library websiteLast updated: 28/04/2023 14:49:13
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