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STAT8004 - Stats & Experimental Design

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Title:Stats & Experimental Design
Long Title:Stats & Experimental Design
Module Code:STAT8004
 
Duration:1 Semester
Credits: 5
NFQ Level:Advanced
Field of Study: Statistics
Valid From: Semester 1 - 2016/17 ( September 2016 )
Module Delivered in 2 programme(s)
Module Coordinator: David Goulding
Module Author: AINE NI SHE
Module Description: This module aims to develop skills in the application of the methods of probability and statistics in engineering and science. The module will allow the student to acquire knowledge, skill and competence in the areas of probability, statistical models, sampling theory, hypothesis testing, design of experiments and regression analysis.
Learning Outcomes
On successful completion of this module the learner will be able to:
LO1 Apply probability models to engineering problems
LO2 Calculate point and interval estimates of population parameters
LO3 Formulate and carry out statistical tests of hypothesis, including analysis of variance procedures.
LO4 Choose an experimental design appropriate to a given problem and perform the analysis on the resultant data.
LO5 Perform regression analysis, both simple and multiple cases.
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).
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
 

Module Content & Assessment

Indicative Content
Probability models
Detailed treatment of the standard probability models including Binomial Poisson, Normal, and their application to Engineering problems
Statistical Inference.
Sampling distributions. Estimation and significance testing; procedures involving normal, t, F and chi-square distributions. Analysis of variance.
Design of experiments
Introduction to the concepts and terminology of experimental design, along with some analysis of designed experiments
Regression Analysis.
Least squares. The simple linear model. Analysis of residuals, coefficient of determination. Analysis of variance for regression. Confidence limits for prediction. Introduction to multiple regression; model selection procedures.
Statistical software
Application of a software package such as Minitab to the different statistical methods covered by this course.
Assessment Breakdown%
Course Work30.00%
End of Module Formal Examination70.00%
Course Work
Assessment Type Assessment Description Outcome addressed % of total Assessment Date
Short Answer Questions In-class test 1,2 15.0 Week 7
Practical/Skills Evaluation Lab Assessment 1,2,3,4 15.0 Week 12
End of Module Formal Examination
Assessment Type Assessment Description Outcome addressed % of total Assessment Date
Formal Exam End-of-Semester Final Examination 1,2,3,4,5 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 Lecture 3.0 Every Week 3.00
Lab Analysis using Statistical Software 1.0 Every Second Week 0.50
Tutorial Review of lecture content, tutorial sheets 1.0 Every Second Week 0.50
Independent & Directed Learning (Non-contact) Review of lecture content, completion of exercises 3.0 Every Week 3.00
Total Hours 8.00
Total Weekly Learner Workload 7.00
Total Weekly Contact Hours 4.00
Workload: Part Time
Workload Type Workload Description Hours Frequency Average Weekly Learner Workload
Lecture Lecture 3.0 Every Week 3.00
Lab Analysis using Statistical Software 1.0 Every Second Week 0.50
Tutorial Review of lecture content, tutorial sheets 1.0 Every Second Week 0.50
Independent & Directed Learning (Non-contact) Review of lecture content, completion of exercises 3.0 Every Week 3.00
Total Hours 8.00
Total Weekly Learner Workload 7.00
Total Weekly Contact Hours 4.00
 

Module Resources

Recommended Book Resources
  • Douglas C. Montgomery, George C. Runger 2011, Applied Statistics and Probability for Engineers, 6th Edition International Student Version, Sixth Edition Ed., Jon Wiley&Sons Hoboken, NJ [ISBN: 9781118744]
Supplementary Book Resources
  • Richard L. Scheaffer, Madhuri S. Mulekar, James T. McClave 2011, Probability & Statistics for Engineers, Fifth Edition Ed., Brooks/Cole Cengage Learning Boston [ISBN: 9780538735902]
  • Jay Devore 2014, Probability and Statistics for Engineeering and the Sciences, Ninth Edition Ed., Brooks Cole [ISBN: 978130525180]
  • Sheldon M. Ross 2014, Introduction to probability and statistics for engineers and scientists, Fifth Edition Ed., Elsevier [ISBN: 9780123948113]
  • Douglas C. Montgomery 2008, Introduction to statistical quality control, Sixth Edition Ed., John Wiley & Sons Hoboken, N.J. [ISBN: 9780470233979]
  • Jiju Antony 2014, Design of Experiments for Engineers and Scientists, Second Edition Ed., Elsevier [ISBN: 9780080994178]
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_ECPEN_8 Bachelor of Engineering (Honours) in Chemical and Biopharmaceutical Engineering 5 Mandatory
CR_EMENG_9 Master of Engineering in Mechanical Engineering 1 Group Elective 1

Cork Institute of Technology
Rossa Avenue, Bishopstown, Cork

Tel: 021-4326100     Fax: 021-4545343
Email: help@cit.edu.ie