Short Title:Mathematics 3
Full Title:Mathematics 3
Module Code:STAT H2003
Credits: 5
NFQ Level:6
Field of Study:Mechanics and metal work
Module Delivered in 5 programme(s)
Module Author:JAMES REILLY
Module Description:The aim of the module Mathematics 3 is to provide the student with a working knowledge of statistical techniques so as to enable them to select and apply such techniques to the solution of engineering problems.
Learning Outcomes
On successful completion of this module the learner will be able to:
LO1 Construct simple truth tables.
LO2 Apply modularity in program design.
LO3 Collect, present, and summarise data.
LO4 Calculate probabilities.
LO5 Explain the application of binomial, Poisson, exponential and normal distributions to problems in reliability engineering, sampling inspection, conformance to specification, and failure times.
LO6 Construct confidence intervals for means and proportions.
LO7 Use hypothesis tests to compare products or processes.
LO8 Predict responses using regression analysis.
LO9 Investigate the correlation between variables.
LO10 Evaluate the capability of a process and construct SPC charts.
Pre-requisite learning
Co-requisite Modules
No Co-requisite modules listed

Module Content & Assessment

Content (The percentage workload breakdown is inidcative and subject to change) %
Programming skills
Simple and compound propositions. Truth tables. Simple logic circuits: AND, OR, NAND, NOR, EXCLUSIVE OR. Modularity in program design; use of built-in I/O and mathematical functions. User defined functions and parameter passing.
Working with data:
Collecting data: tallies. Organising data: frequency tables. Graphs: frequency curves, and time series. Population and sample: inference. Summary statistics: mean, median, mode, range, standard deviation, coefficient of variation.
Definition of probability. Calculating probabilities. Permutations and combinations. The laws of probability. Reliability engineering: components in series and in parallel.
Discrete probability distributions:
The binomial distribution: defectives. The Poisson distribution: defects, breakdowns.
Continuous probability distributions:
The exponential distribution: failure times. The normal distribution: percentage out-of-specification. Typical non-normal patterns and their causes. Process Capability. Statistical Process Control: X-Bar charts, np charts and c charts.
The addition of variances. The central limit theorem. Confidence intervals for means and proportions.
Testing theories:
Tests of population means and proportions.
Regression and Correlation:
Scatterplots. Correlation coefficient. Coefficient of determination. Regression equation. Prediction: interpolation and extrapolation.
Assessment Breakdown%
Course Work40.00%
End of Module Formal Examination60.00%
Course Work
Assessment Type Assessment Description Outcome addressed % of total Assessment Date
Continuous Assessment Students will carry out a number of independent and group projects involving data collection and analysis, and will present results and conclusions in written form and through an oral presentation. 3,6 20.00 Ongoing
Continuous Assessment Exercises and laboratory tests on the application of programming. 1,2 10.00 n/a
Short Answer Questions High threshold "key skills" quiz testing key basic mathematical techniques. (First opportunity to do the test is in week 1.) 5,8 10.00 Ongoing
End of Module Formal Examination
Assessment Type Assessment Description Outcome addressed % of total Assessment Date
Formal Exam End-of-Semester Final Examination 3,4,5,6,7,8,9,10 60.00 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.

IT Tallaght 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 Lectures, demonstrations, exercises, feedback. 3.00 Every Week 3.00
Lab Programming labs 1.00 Every Week 1.00
Independent Learning Time Assigned project work, problem solving. 3.00 Every Week 3.00
Total Weekly Learner Workload 7.00
Total Weekly Contact Hours 4.00
This module has no Part Time workload.

Module Resources

Required Book Resources
  • James Reilly 2018, Applied Statistics, 2nd Ed.,
Recommended Book Resources
  • Brian Hahn and Daniel Valentine 2016, Essential MATLAB for Engineers and Scientists, 6th Ed., Academic Press [ISBN: 0081008775]
  • Kenneth Koehler 2016, Snedecor and Cochran's Statistical Methods, 9th Edn Ed., Blackwell [ISBN: 0813808642]
  • Barbara Illowsky and Susan Dean 2017, Introductory Statistics,
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
TA_EBIOM_B B.Eng (Hons) in Biomedical Design 3 Mandatory
TA_EAMEC_B B.Eng(Hons) in Mechanical Engineering [Ab Initio] 3 Mandatory
TA_EBIOM_D Bachelor of Engineering in Biomedical Design 3 Mandatory
TA_EAMEC_D Bachelor of Engineering in Mechanical Engineering 3 Mandatory
TA_EAUTO_D Bachelor of Mechanical Engineering (Automation) 3 Mandatory