Registry
Module Specifications
Archived Version 2023 - 2024
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Description The aim of this module is introduce and improve the specific skills needed for research (reading, critical analysis of literature, writing and communication) and to understand and apply data analysis to experimental/theoretical research problems (methodology, statistics, experimental design and advice about how to do research). This will not only benefit students when doing their MSc project but also in monitoring results in industry. Students are expected to contribute to the module, engage in assignments through both online and/or class room delivery. | |||||||||||||||||||||||||||||||||||||||||
Learning Outcomes 1. Relate statistics and the laws of probability to research methodological techniques. 2. Identify continuous random variables and the normal distribution, test for normality, hypotheses testing, inference, variance and regression. 3. Understand statistical Design and analysis of experiments and use Design Expert to analyse enginnering/scientific experiments. 4. Apply and understand Research Methodologies such as: Citation and Referencing, critically analysing publications, Ethical considerations, Case Studies and Dissemination of Research | |||||||||||||||||||||||||||||||||||||||||
All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml |
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Indicative Content and
Learning Activities Indicative SyllabusResearch Statistics and Probability, Continuous random variables and the normal distribution.n/aInference: The Central Limit Theorem. Confidence intervals for the mean with variance both known and unknown. Testing for normality. Confidence intervals for the variance. Confidence intervals for proportions. Tests of hypotheses for a single sample. Inference for two samples: inference for the difference in means for two Normal distributions, variance both known and unknown.n/aRegression: Simple linear regression and correlation. Multiple linear regression, Design and analysis of single factor experiments: Designing engineering experiments. The completely randomised single-factor experiment. The Random Effects Model. Randomised complete block design. Design of experiments with two factors.n/aWriting Skills; How to write a thesis and Conference/Journal papers, Citation and Referencing, Literature search, critically analyse publications, Impact Factors, Ethical considerations, Case Studiesn/aCommunication: Presentation Skills and Dissemination of Research | |||||||||||||||||||||||||||||||||||||||||
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Indicative Reading List
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Other Resources None | |||||||||||||||||||||||||||||||||||||||||
Programme or List of Programmes | |||||||||||||||||||||||||||||||||||||||||
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