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MATH6038 - Mathematics for Science 2.2

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Title:Mathematics for Science 2.2
Long Title:Mathematics for Science 2.2 with Maple
Module Code:MATH6038
 
Credits: 5
NFQ Level:Fundamental
Field of Study: Mathematics
Valid From: Semester 1 - 2009/10 ( September 2009 )
Module Delivered in 3 programme(s)
Module Coordinator: AINE NI SHE
Module Author: MICHAEL BRENNAN
Module Description: This modules involves the study of matrices, statistics and probability distributions.
Learning Outcomes
On successful completion of this module the learner will be able to:
LO1 Use matrix techniques to solve systems of equations
LO2 Calculate and interpret measures of central tendency and measures of dispersion
LO3 Calculate probabilities using standard distributions
LO4 Construct and interpret quality control charts
LO5 Use the Maple package to explore and reinforce mathematical concepts
Pre-requisite learning
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 CIT module(s) it also allows for learning (in another module or modules) which is equivalent to the learning specified in the named module(s).
No recommendations listed
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
Co-requisites
No Co Requisites listed
 

Module Content & Assessment

Indicative Content
Matrix Algebra
Matrix operations, properties of matrix operations, determinants, properties of determinants, row operations, Gaussian elimination, inverse matrices, solving linear system of equations, investigation of the solution space of linear system of equations.
Probability and Statistics
Presentation and analysis of data. Measures of central tendency; mean, mode and median. Measures of dispersion; range variance and standard deviation. Sample space, compound events, conditional probability, independent events, reliability block diagrams,Bayes Rule. Random variables, binomial, Poisson and Normal distributions. Introduction to sampling, confidence intervals for large and small samples. Constuct and interpret quality control charts.
Assessment Breakdown%
Course Work30.00%
End of Module Formal Examination70.00%
Course Work
Assessment Type Assessment Description Outcome addressed % of total Assessment Date
Other One hour written exam 1,2 20.0 Week 7
Practical/Skills Evaluation Maple Lab 5 10.0 Every Week
End of Module Formal Examination
Assessment Type Assessment Description Outcome addressed % of total Assessment Date
Formal Exam End-of-Semester Final Examination 1,2,3,4 70.0 End-of-Semester
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 institute reserves the right to alter the nature and timings of assessment

 

Module Workload

Workload: Full Time
Workload Type Workload Description Hours Frequency Average Weekly Learner Workload
Lecture Conventional Lecture 3.0 Every Week 3.00
Tutorial Based on Exercise Sheets 1.0 Every Week 1.00
Lab Laboratory 1.0 Every Week 1.00
Independent & Directed Learning (Non-contact) No Description 2.0 Every Week 2.00
Total Hours 7.00
Total Weekly Learner Workload 7.00
Total Weekly Contact Hours 5.00
Workload: Part Time
Workload Type Workload Description Hours Frequency Average Weekly Learner Workload
Lecture Conventional Lecture 3.0 Every Week 3.00
Lecturer-Supervised Learning (Contact) Based on Exercise Sheets 1.0 Every Week 1.00
Lab Laboratory 1.0 Every Week 1.00
Independent & Directed Learning (Non-contact) No Description 2.0 Every Week 2.00
Total Hours 7.00
Total Weekly Learner Workload 7.00
Total Weekly Contact Hours 5.00
 

Module Resources

Recommended Book Resources
  • John Bird 2006, Higher Engineering Mathematics, Fifth Ed., Newnes
Supplementary Book Resources
  • Anthony Croft & Robert Davison 1998, Mathematics for Engineers-A Modern Interactive Approach, Pearson [ISBN: 0-13120193-X]
This module does not have any article/paper resources
Other Resources
 

Module Delivered in

Programme Code Programme Semester Delivery
CR_SCISY_8 Bachelor of Science (Honours) in Computerised Instrument Systems 4 Mandatory
CR_SPHYS_7 Bachelor of Science in Applied Physics and Instrumentation 4 Mandatory
CR_SPHYS_6 Higher Certificate in Applied Physics and Instrumentation 4 Mandatory

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Email: help@cit.edu.ie