2023/24 Undergraduate Module Catalogue

SOEE1312 Advanced Mathematics 2

10 creditsClass Size: 42

Module manager: Graham Mann
Email: G.W.Mann@leeds.ac.uk

Taught: Semester 2 (Jan to Jun) View Timetable

Year running 2023/24

Pre-requisite qualifications

SOEE1302 or students with A-level pure maths or further maths (or equivalent) may take this module with approval from the module leader and your programme manager.

Pre-requisites

SOEE1302

Advanced Mathematics 1

This module is mutually exclusive with

SOEE2430

Adv Maths for Scientists

Module replaces

SOEE1311 Advanced Mathematics for Environmental and Geophysical Scientists

This module is not approved as a discovery module

Objectives

On completion of this module, students will be able to:
1. determine the partial derivatives and extrema of a function
2. apply the grad operator (div, grad, curl)
3. solve partial differential equations
4. Fourier analysis
5. introduction to multi-dimensional integration.

Skills outcomes
The module places considerable emphasis on:
- developing the skills necessary for self-managed and lifelong learning (eg working independently, time management and organisation skills);
- recognising and using subject-specific theories, paradigms, concepts and principles;
- applying knowledge and understanding to address familiar and unfamiliar problems;
- solving numerical problems using computer and non-computer based techniques;
- developing the skills necessary for self-managed and lifelong learning (eg working independently, time management and organisation skills).

The module places moderate emphasis on:
- analysing, synthesising and summarising information critically, including prior research;
- preparing, processing, interpreting and presenting data, using appropriate qualitative and quantitative techniques and packages;
- using the Internet critically as a means of communication and a source of information;
- identifying and working towards targets for personal, academic and career development.

The module places some emphasis on:
- collecting and integrating several lines of evidence to formulate and test hypotheses;
- receiving and responding to a variety of information sources (eg textual numerical, verbal, graphical);
- developing an adaptable and flexible approach to study and work.

Syllabus

1. Partial derivatives and extrema
2. Vector calculus
3. Partial differential equations
4. Fourier analysis
5. Introduction to multi-dimensional integration.

Teaching methods

Delivery type	Number	Length hours	Student hours
Lecture	11	1.00	11.00
Practical	11	2.00	22.00
Private study hours			67.00
Total Contact hours			33.00
Total hours (100hr per 10 credits)			100.00

Private study

- Assessed exercises: 6 hours
- Non-assessed exercises: 46 hours
- Private study and revision: 15 hours.

Opportunities for Formative Feedback

- Example sheets with model solutions are provided at the start of each topic.
- Students study these as part of the learning process.
- Further examples sheets (not assessed) are provided for students to work on independently.
- Assistance with these may be given at practical classes but solutions are only provided after the topic is completed.

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
In-course Assessment	Assessed set of mathematical problems to solve	15.00
Total percentage (Assessment Coursework)		15.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Exams

Exam type	Exam duration	% of formal assessment
Online Time-Limited assessment	1 hr 30 mins	85.00
Total percentage (Assessment Exams)		85.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Reading list

There is no reading list for this module

Last updated: 14/02/2024

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