2024/25 Undergraduate Module Catalogue

LUBS1285 Mathematics and Statistics for Economics and Business 1B

10 creditsClass Size: 700

Module manager: Henry Duncanson
Email: H.Duncanson@leeds.ac.uk

Taught: Semester 2 (Jan to Jun) View Timetable

Year running 2024/25

Pre-requisite qualifications

LUBS1275 Mathematics and Statistics for Economics and Business 1A
OR
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 website

Last updated: 29/04/2024 16:16:20

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