Module Details

Module Code: MATH6043
Title: Technological Mathematics 221
Long Title: Tech Mathematics 221 for Elect. Eng
NFQ Level: Fundamental
Valid From: Semester 1 - 2020/21 ( September 2020 )
Duration: 1 Semester
Credits: 5
Field of Study: 4610 - Mathematics
Module Delivered in: 5 programme(s)
Module Description: This module involves the study of both first and second order differential equations with a focus on electrical applications. An introduction to linear algebra and probability distributions completes the module.
 
Learning Outcomes
On successful completion of this module the learner will be able to:
# Learning Outcome Description
LO1 Solve first and second order differential equations using classical methods.
LO2 Evaluate determinants and perform matrix operations.
LO3 Evaluate probabilities associated with simple and composite events using the basic rules of probability.
LO4 Recognise and solve probability problems associated with selected discrete and continuous probability distributions.
Dependencies
Module Recommendations

This is prior learning (or a practical skill) that is strongly recommended before enrolment in this module. You may enrol in this module if you have not acquired the recommended learning but you will have considerable difficulty in passing (i.e. achieving the learning outcomes of) the module. While the prior learning is expressed as named MTU module(s) it also allows for learning (in another module or modules) which is equivalent to the learning specified in the named module(s).
14749 MATH6041 Technological Mathematics 220
Incompatible Modules
These are modules which have learning outcomes that are too similar to the learning outcomes of this module. You may not earn additional credit for the same learning and therefore you may not enrol in this module if you have successfully completed any modules in the incompatible list.
No incompatible modules listed
Co-requisite Modules
No Co-requisite modules listed
Requirements

This is prior learning (or a practical skill) that is mandatory before enrolment in this module is allowed. You may not enrol on this module if you have not acquired the learning specified in this section.
No requirements listed
 
Indicative Content
Differential Equations
Methods used to solve first order differential equations: direct integration, variables separable, integrating factor. Solution of second order linear differential equations with constant coefficients. Method of undetermined coefficients. Applications including electrical circuits.
Linear Algebra
Matrix definition and notation. Matrix algebra. Matrix transpose. Symmetric matrix. Determinants. Matrix Inverse. Cramer's Rule. Solution set of a linear system of equations. Singular matrix and inconsistent equations.
Probability
Bayesian and Frequentist definition of probability. Introduction to the basic laws of probability and the solution of composite probability problems using the “AND” and “OR” laws of probability for mutually exclusive and independent events
Probability Distributions
Introduction to discrete and continuous probability distributions. Definition and appropriate use of the Binomial, Poisson and Normal Gaussian distributions. Expected values and variances of distributions. Approximations of distributions.
Module Content & Assessment
Assessment Breakdown%
Coursework30.00%
End of Module Formal Examination70.00%

Assessments

Coursework
Assessment Type Short Answer Questions % of Total Mark 15
Timing Week 6 Learning Outcomes 1
Assessment Description
Class assessment
Assessment Type Short Answer Questions % of Total Mark 15
Timing Week 10 Learning Outcomes 2,3
Assessment Description
Class assessment
End of Module Formal Examination
Assessment Type Formal Exam % of Total Mark 70
Timing End-of-Semester Learning Outcomes 1,2,3,4
Assessment Description
End-of-Semester Final Examination
Reassessment Requirement
Repeat examination
Reassessment of this module will consist of a repeat examination. It is possible that there will also be a requirement to be reassessed in a coursework element.

The University reserves the right to alter the nature and timings of assessment

 

Module Workload

Workload: Full Time
Workload Type Contact Type Workload Description Frequency Average Weekly Learner Workload Hours
Lecture Contact Delivery of course material Every Week 3.00 3
Tutorial Contact Problem solving including group work Every Week 1.00 1
Independent & Directed Learning (Non-contact) Non Contact Study of lecture notes, exercise sheets and problem solving Every Week 3.00 3
Total Hours 7.00
Total Weekly Learner Workload 7.00
Total Weekly Contact Hours 4.00
Workload: Part Time
Workload Type Contact Type Workload Description Frequency Average Weekly Learner Workload Hours
Lecture Contact Delivery of course material Every Week 3.00 3
Independent & Directed Learning (Non-contact) Non Contact Study of lecture notes, exercise sheets and problem solving Every Week 4.00 4
Total Hours 7.00
Total Weekly Learner Workload 7.00
Total Weekly Contact Hours 3.00
 
Module Resources
Recommended Book Resources
  • John Bird. (2017), Higher Engineering Mathematics, 8th Edition. Routledge, Abingdon, [ISBN: 1138673579].
Supplementary Book Resources
  • K A Stroud. (2013), Engineering Mathematics, 7th Edition. Macmillan, London, [ISBN: 1137031204].
This module does not have any article/paper resources
Other Resources
 
Module Delivered in
Programme Code Programme Semester Delivery
CR_EEPSY_8 Bachelor of Engineering (Honours) in Electrical Engineering 4 Mandatory
CR_EELES_8 Bachelor of Engineering (Honours) in Electronic Engineering 4 Mandatory
CR_ESMPR_8 Bachelor of Engineering (Honours) in Smart Product Engineering 4 Mandatory
CR_EELEC_7 Bachelor of Engineering in Electrical Engineering 4 Mandatory
CR_EELXE_7 Bachelor of Engineering in Electronic Engineering 4 Mandatory