NG1S502 - Computational Techniques 01 Jul 2021 - 31 Aug 2027 | Version 1
Associated Module Information
| Module Code: | NG1S502 | ||
|---|---|---|---|
| Module Title: | Computational Techniques | ||
| Faculty: | Faculty of Computing, Engineering and Science | ||
| Faculty Group: | Engineering | ||
| Faculty Sub Group: | Aeronautical Engineering | ||
| Module Leader: | Gary Dornan | ||
| Module Team: | David Scammell | ||
| First Intended Intake: | SEP 2026 | Final Year of Intake: | 2026 |
| Date Closed: | |||
| Credit Value: | 20 | Credit Level: | 4 |
| Language: | English | ||
| Percentage of Module Taught in Welsh: | 0 | ||
| Equivalent Module: | |||
| HECOS codes: | 100403 - mathematics | 100406 - statistics | |
| HECOS Code Weighting: | 70 | 30 | |
Document Version Information
| Version | 1 |
|---|---|
| Valid From | 01 Jul 2021 |
| Valid To | 31 Aug 2027 |
Module Aims
This module aims to provide students with the mathematical skills needed and understand the relevance of mathematics in solving engineering problems and introduce students to a range of statistical methods applied to the collection, analysis, and interpretation of data.
Content Summary
Linear, simultaneous linear and quadratic equations. Factorisation, expansion and simplification of algebraic expressions. Rearrangement of formulae. Indices and logarithms. The exponential function.
Trigonometric and Inverse trigonometric functions and their graphs, Pythagoras theorem, The sine and cosine rules, simple trigonometric identities, and equations
Equation of a straight line. Plotting straight line graphs. Reduction of other functions to straight line form. Least squares approximations
Concept of differentiation, Differentiation of simple functions. The product, quotient, and function of a function rules. Maxima and minima. Velocity and acceleration.
Integration as the reverse of differentiation, integration using standard forms, simple substitutions, and parts. Numerical integration. Application to area, volume and second moments of area.
Graphical display of data. Calculation of measures of central tendency (mean, median, mode), measures of dispersion (standard deviation and variance) and interquartile range. The binomial, Poisson, and normal distributions.
Learning and Teaching Methods
| Activity Type | Hours |
|---|---|
| Practical classes and workshops | 50 |
| Independent Study | 110 |
| Directed Study | 24 |
| Problem / challenge based learning | 16 |
| Total Hours Selected | 200 |
Learning Outcomes
| # | Learning Outcome |
|---|---|
| LO1 | Students will be able to evaluate and manipulate problems using Algebra, Trigonometry, Calculus, Geometry and Statistical processes. |
| LO2 | Students will demonstrate understanding and interpretation of the statistics and mathematics applied in modern industrial Manufacturing and Engineering. |
Module Requisites
N/A
Assessment Criteria
| Assessment Category | Assessment Type | Description | Duration | Word Count | Weight (%) | Best of? | Pass Mark |
|---|---|---|---|---|---|---|---|
| Asynchronous Assessment | Portfolio 1 | Report and Poster Presentation | 0 | N/A | 100 | No | 40 |
Assessment Matrix
| Assessment Type | Learning Outcomes | ||
|---|---|---|---|
| LO1 | LO2 | ||
| Portfolio 1 | ✔ | ✔ | |