Module Details
| Module Code: |
STAT8005 |
| Title: |
Statistics for Engineering
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|
Long Title:
|
Statistics for Engineering
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| NFQ Level: |
Advanced |
| Valid From: |
Semester 1 - 2019/20 ( September 2019 ) |
| Field of Study: |
4620 - Statistics
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| Module Description: |
This module will apply statistics and probability distributions to modern day engineering problems. It will develop graphical visualisation methods, probability theory and distributions. The module will develop knowledge, skill and competence of sampling theory and hypothesis testing.
|
| Learning Outcomes |
| On successful completion of this module the learner will be able to: |
| # |
Learning Outcome Description |
| LO1 |
Use the methods of descriptive statistics |
| LO2 |
Apply probability and probability models to engineering problems |
| LO3 |
Compute and interpret point and interval estimates of population parameters |
| LO4 |
Conduct a variety of statistical tests of hypothesis |
| LO5 |
Perform correlation and regression analysis |
| 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).
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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.
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| No incompatible modules listed |
Co-requisite Modules
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| 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.
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| No requirements listed |
| Indicative Content |
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Descriptive statistics
Graphical and numerical methods of data description
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Probability and probability distributions.
Review of laws of probability and of Binomial, Poisson, Normal and Exponential distributions. Means and variances of random variables. Distribution of sums and differences of random variables.
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Sampling Theory.
Sampling distributions of means, proportions, differences of means, differences of proportions, variances and ratios of variances. The Central Limit Theorem. Concept of standard error. Application to SPC charts.
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Statistical Inference.
Estimation, point estimates and confidence intervals. Necessary sample size. Significance tests: null and alternative hypotheses, test statistic, level of significance, p-value. Z-tests, t-tests, F-tests, chi-square tests, paired comparisons, parametric versus non-parametric tests.
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Regression and Correlation
Simple linear regression, method of least squares, coefficient of determination, confidence intervals and prediction intervals, correlations coefficient, significance tests in regression and correlation
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Statistical software.
Application of a package such as MINITAB to the different aspects of statistical analysis dealt with in this course.
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Module Content & Assessment
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| Assessment Breakdown | % |
|---|
| Coursework | 100.00% |
Assessments
| No End of Module Formal 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 |
No Description |
Every Week |
3.00 |
3 |
| Lab |
Contact |
No Description |
Every Second Week |
0.50 |
1 |
| Tutorial |
Contact |
No Description |
Every Second Week |
0.50 |
1 |
| Independent & Directed Learning (Non-contact) |
Non Contact |
No Description |
Every Week |
3.00 |
3 |
| Total Hours |
8.00 |
| Total Weekly Learner Workload |
7.00 |
| Total Weekly Contact Hours |
4.00 |
| This module has no Part Time workload. |
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Module Resources
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| Recommended Book Resources |
|---|
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Douglas C. Montgomery, George C. Runger.. (2018), Applied Statistics and Probability for Engineers, 7th Edition. John Wiley & Sons,, Hoboken,NJ, [ISBN: 9781119400363].
| | Supplementary Book Resources |
|---|
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Richard L. Scheaffer, Madhuri S. Mulekar, James T. McClave.. (2011), Probability & Statistics for Engineers, 5th Edition. Brooks/Cole Cengage Learning, Boston, MA, [ISBN: 9780538735902].
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Jay L. Devore.. (2015), Probability and statistics for engineering and the sciences, 9th Edition. Cengage Learning, Florence, [ISBN: 9781305251809].
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Sheldon M. Ross. (2014), Introduction to Probability and Statistics for Engineers and Scientists, 5th Edition. Academic Press, [ISBN: 9780123948113].
| | This module does not have any article/paper resources |
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| This module does not have any other resources |
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