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Module Specifications.

Current Academic Year 2024 - 2025

All Module information is indicative, and this portal is an interim interface pending the full upgrade of Coursebuilder and subsequent integration to the new DCU Student Information System (DCU Key).

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Date posted: September 2024

Module Title Research Practice & Methodology
Module Code MM533 (ITS) / MEC1057 (Banner)
Faculty Engineering & Computing School Mechanical & Manufacturing Eng
Module Co-ordinatorPaul Young
Module TeachersJeremiah Murphy, Khaled Benyounis, Nicholas Dunne
NFQ level 9 Credit Rating 7.5
Pre-requisite Not Available
Co-requisite Not Available
Compatibles Not Available
Incompatibles Not Available
None
Array
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



Workload Full-time hours per semester
Type Hours Description
Lecture36Lecture Based
Lecture36Lecture Based
Tutorial24Studio/Tutorial
Tutorial24Studio/Tutorial
Assignment Completion90No Description
Assignment Completion90No Description
Independent Study37.5No Description
Independent Study37.5No Description
Total Workload: 375

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

Indicative Content and Learning Activities

Indicative Syllabus
Research Statistics and Probability, Continuous random variables and the normal distribution.

n/a
Inference: 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/a
Regression: 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/a
Writing Skills; How to write a thesis and Conference/Journal papers, Citation and Referencing, Literature search, critically analyse publications, Impact Factors, Ethical considerations, Case Studies

n/a
Communication: Presentation Skills and Dissemination of Research

Assessment Breakdown
Continuous Assessment50% Examination Weight50%
Course Work Breakdown
TypeDescription% of totalAssessment Date
ProjectSubmission of a 6-page Conference paper:- Involves research, compilation, design of experiments, analysis of data on a research topic25%Week 30
In Class TestStatistical problem based class test25%Week 29
Reassessment Requirement Type
Resit arrangements are explained by the following categories:
Resit category 1: A resit is available for both* components of the module.
Resit category 2: No resit is available for a 100% continuous assessment module.
Resit category 3: No resit is available for the continuous assessment component where there is a continuous assessment and examination element.
* ‘Both’ is used in the context of the module having a Continuous Assessment/Examination split; where the module is 100% continuous assessment, there will also be a resit of the assessment
This module is category 1
Indicative Reading List

  • Helstrom, Carl W.: 0, Probability and stochastic processes for engineers,
  • Miller, Irwin: 0, Probability and statistics for engineers,
  • Clarke, A.B.: 0, Probability and random processes : a first course,
  • Meyer, S.L.: 0, Data analysis for scientists and engineers,
  • Hamming, R.W.: 0, The art of probability for scientists and engineers,
  • Walpole, R.E.: 0, Probability and statistics for engineers and scientists,
  • Montgomery, D.C.: 0, Applied statistics and probability for engineers,
  • Murray, R.,: 0, How to write a Thesis,
  • Moore, N: 0, How to do research : the complete guide to designing and managing research projects,
  • Kerr, A.W.: 0, Doing statistics with SPSS11,
  • Puri, B.K.,: 0, SPSS in practice : an illustrated guide,
Other Resources

None

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