MATH7019 - Applied Technological Math 311

Module Details

Module Code: MATH7019
Title: Applied Technological Math 311
Long Title: Applied Technological Math 311
NFQ Level: Intermediate
Valid From: Semester 1 - 2019/20 ( September 2019 )
Duration: 1 Semester
Credits: 5
Field of Study: 4610 - Mathematics
Module Delivered in: 2 programme(s)
Module Description: This module covers: curve fitting; static beam differential equations; Taylor series; normal distributions, statistical inference.
 
Learning Outcomes
On successful completion of this module the learner will be able to:
# Learning Outcome Description
LO1 Find and use the curve of best fit to a data set.
LO2 Understand the concept of a differential equation and solve static beam differential equations.
LO3 Use Taylor Series to approximate solutions of differential equations.
LO4 Use the normal distribution to solve engineering problems, and understand the concepts of sampling and hypothesis testing.
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).
10145 MATH6040 Technological Mathematics 201
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
Curve Fitting & Mathematical Modelling
Applications of curve fitting. Lagrange Interpolation. Determination of curves of best-fit in the least squares sense. Non-linear laws. Correlation. Use of models.
Static Beam Differential Equations
Step functions. Static beam differential equations including simply supported, fixed ends, and cantilevers.
Taylor Series
Review of single variable calculus. Taylor Series of one variable. Euler Method and Three Term Taylor. Review of functions of several variables and partial differentiation. Differentials with applications to analysis of rounding error.
Probability & Statistics
Random variables. Laws of probability. Normal distribution. Applications to engineering problems. Sampling, and Hypothesis Testing, for population means and population proportions.
Module Content & Assessment
Assessment Breakdown%
Coursework30.00%
End of Module Formal Examination70.00%

Assessments

Coursework
Assessment Type Written Report % of Total Mark 15
Timing Week 5 Learning Outcomes 1
Assessment Description
Short report utilising a software package such as Microsoft Excel to assist in fitting curves to civil engineering data sets.
Assessment Type Written Report % of Total Mark 15
Timing Week 10 Learning Outcomes 2,3
Assessment Description
Short report investigating static beam differential equations; to include use of a software package such as Microsoft Excel to find numerical solutions.
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 Lecture Every Week 3.00 3
Tutorial Contact Based on exercises Every Week 1.00 1
Independent & Directed Learning (Non-contact) Non Contact Review of lecture material, completion of exercises 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 Lecture Every Week 2.00 2
Tutorial Contact Based on exercises Every Second Week 1.00 2
Independent & Directed Learning (Non-contact) Non Contact Review of lecture material, completion of exercies Every Week 4.00 4
Total Hours 8.00
Total Weekly Learner Workload 7.00
Total Weekly Contact Hours 3.00
 
Module Resources
Recommended Book Resources
  • K A Stroud, Dexter J Booth. (2013), Engineering Mathematics, 7th. Palgrave Macmillan, Hampshire, [ISBN: 978113703120].
Supplementary Book Resources
  • John Bird. (2017), Higher Engineering Mathematics, 7th. Routledge/Taylor & Francis, London, New York, [ISBN: 9781138673571].
  • Douglas C. Montgomery, George C. Runger. (2014), Applied Statistics and Probability for Engineers, 6th. John Wiley & Sons Inc, New York, [ISBN: 9781118744123].
This module does not have any article/paper resources
This module does not have any other resources
 
Module Delivered in
Programme Code Programme Semester Delivery
CR_CCIVL_7 Bachelor of Engineering in Civil Engineering 5 Mandatory
CR_CENVI_7 Bachelor of Engineering in Environmental Engineering 5 Mandatory