NUMERICAL AND STATISTICAL METHODS - 2022/3

Module Overview

Civil Engineers routinely make use of software tools for calculations on physical systems, ranging from structural analysis, to soil mechanics and fluid dynamics. This module provides an introduction to the numerical and statistical methods underlying many of these tools, including Finite Element and Finite Difference Methods as well as linear regression.

The module is hands-on: students will be introduced to MATLAB and learn to write their own programs to apply the methods encountered in the module.

Module provider

Sustainability, Civil & Env Engineering

Module Leader

HAGEN-ZANKER Alex (Sust & CEE)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 5

Module cap (Maximum number of students): N/A

Module Availability

Semester 1

Prerequisites / Co-requisites

N/A

Module content

The module sits within the core subject of mathematic and covers the following areas:

• Fundamental programming concepts: variables, functions, control structures, vector and matrix data structures


• Syntax, semantics and good programming practice.


• Using the MATLAB programming language and integrated development environment


• Solution of Ordinary Differential Equations by Runge-Kutta and associated methods


• Solution methods for simultaneous linear equations


• Principles and application of the Finite Difference Method for solving Ordinary and Partial Differential Equations


• Principles and application of the Finite Element Method applied on truss structures


• Principles and application of (multiple) linear regression, including confidence and significance

Assessment pattern

Alternative Assessment

N/A

Assessment Strategy

Summative assessment

The summative assessment for this module consists of two coursework assignment and an exam. In the first coursework assignment, students demonstrate fundamental programming skills in MATLAB, including the use of functions, variable, matrix and vector data structures, control structures and plotting (learning outcomes 003 and 005). In the second coursework, students apply their programming skills to implement a numerical method that they have independently researched (learning outcomes 004 and 005). The end-of-semester exam assesses the element of theoretical understanding of numerical and statistical methods (learning outcomes 001 and 002).

Formative assessment and feedback

During computer lab based tutorials students have an opportunity to receive verbal feedback on their work. Additionally, students can test their understanding and get immediate feedback through formative assessment in the form of weekly multiple-choice tests. 

Module aims

• Knowledge and experience of the use of standard numerical and statistical methods to solve complex engineering problems
• Knowledge and experience of using computer programming as a tool to solve engineering problems

Learning outcomes

Methods of Teaching / Learning

Lecture notes – and supporting captured content – are used to introduce key concepts and theoretical background. The main learning however, will take place as students complete weekly exercises that bring the newly learned concepts and knowledge to practice. Weekly tutorial sessions are used to provide feedback and discuss these exercises. The first four weeks of the module are dedicated to programming fundamentals. In these weeks the tutorials are longer than usual (two hours instead of one) because of the importance of feedback in this stage of learning. The coursework provides further exercise in developing programming skills and the ability to use these skills to solve numerical problems. A staggered approach is followed, where the first coursework assignment covers fundamentals and the second requires independent inquiry and application of techniques. Weekly seminars are used to reflect on learning including coursework activity, address and re-emphasize salient points in the captured content, provide additional context and give guidance on learning activities.

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list

https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: ENG2106

Other information

Surrey's Curriculum Framework is committed to developing graduates with strengths in Employability, Digital Capabilities, Global and Cultural Capabilities, Sustainability and Resourcefulness and Resilience. This module is designed to allow students to develop knowledge, skills and capabilities in the following areas:

Digital Capabilities: As a module with a strong focus on numerical methods and computer programming, the development of Digital Capabilities is central.

Resourcefulness and Resilience: The coursework requires proactive engagement with technical literature to gain knowledge on a new topic with sufficient depth to then use the knowledge to solve a problem. This emphasis on the development of skills more than factual knowledge resonates well with the Resourcefulness and Resilience pillar of the framework.

Programmes this module appears in

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2022/3 academic year.