Durham University
Programme and Module Handbook

Undergraduate Programme and Module Handbook 2025-2026

Module ENGI2211: Engineering Mathematics 2

Department: Engineering

ENGI2211: Engineering Mathematics 2

Type Tied Level 2 Credits 20 Availability Available in 2025/2026 Module Cap Location Durham
Tied to H100
Tied to H103
Tied to H105
Tied to H106
Tied to H107
Tied to H108
Tied to H211
Tied to H212
Tied to H213
Tied to H214
Tied to H215
Tied to H216
Tied to H311
Tied to H312
Tied to H313
Tied to H314
Tied to H315
Tied to H316
Tied to H411
Tied to H412
Tied to H413
Tied to H511
Tied to H512
Tied to H513
Tied to H514
Tied to H515
Tied to H516
Tied to H711
Tied to H712
Tied to H713
Tied to H714
Tied to H715
Tied to H716
Tied to H811
Tied to H812
Tied to H813
Tied to H911
Tied to H912
Tied to H913

Prerequisites

  • MATH1551

Corequisites

  • None

Excluded Combination of Modules

  • None

Aims

  • To provide a working knowledge of probability and statistics and advanced mathematical methods for modelling engineering problems.

Content

  • Lecture courses: Probability and Statistics; and Numerical Methods
  • Academic advisor meetings

Learning Outcomes

Subject-specific Knowledge:
  • Probability and statistics for engineers
  • Advanced mathematical methods for engineering problems
  • AHEP4 Learning Outcomes: In order to satisfy Professional Engineering Institution (PEI) accreditation requirements the following Accreditation of Higher Education Programmes (AHEP4) Learning Outcomes are assessed within this module:
  • C1. Apply knowledge of mathematics, statistics, natural science and engineering principles to the solution of complex problems (assessed by coursework and exam).
  • C2. Analyse complex problems to reach substantiated conclusions using first principles of mathematics, statistics, natural science and engineering principles (assessed by coursework and exam).
  • C3. Select and apply appropriate computational and analytical techniques to model complex problems, recognising the limitations of the techniques employed (assessed by coursework and exam).
Subject-specific Skills:
  • Application of data analysis techniques using statistics and numerical methods
Key Skills:
  • Numerical skills
  • Time and resource management

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

  • The courses in Probability and Statistics and Numerical Methods are covered in lectures, and are reinforced by regular problem sheets, leading to the required problem solving capability.
  • Assessment is through coursework which enables each student to demonstrate an ability to analyse and solve complex and detailed problems.
  • Students are encouraged to make use of staff 'Surgeries' (otherwise "Office Hours") to discuss any aspect of the module with teaching staff on a one-to-one basis. These are sign-up sessions available for up to one hour per week.
  • Tutorial sessions form part of the department’s Academic Adviser programme.

Teaching Methods and Learning Hours

Activity Number Frequency Duration Total/Hours
Lectures 40 2 per week 1 hour 40
Surgeries 20 As required, weekly sign-ups throughout the year Optional attendance as required 10
Revision Classes 1 1 hour 1
Tutorials 7 1 hour 7
Preparation and Reading 142
Total 200

Summative Assessment

Component: Coursework Component Weighting: 30%
Element Length / duration Element Weighting Resit Opportunity
Assignment 100% Yes
Component: Written examination Component Weighting: 70%
Element Length / duration Element Weighting Resit Opportunity
On Campus Written Examination 2 hours 100% Yes

Formative Assessment:

Formative assessment is provided by means of compulsory formative problem sheets.


Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University