Module: Research Practice & Methodology

Module Specifications..

Current Academic Year 2023 - 2024

Please note that this information is subject to change.

Module Title	Research Practice & Methodology
Module Code	MM533
School	School of Mechanical and Manufacturing Engineering
Module Co-ordinator	Semester 1: Nicholas Dunne Semester 2: Nicholas Dunne Autumn: Nicholas Dunne
Module Teachers	Jeremiah Murphy Khaled Benyounis Nicholas Dunne
NFQ level	9	Credit Rating	7.5
Pre-requisite	None
Co-requisite	None
Compatibles	None
Incompatibles	None

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

*Type*	*Hours*	*Description*
Workload	Full-time hours per semester
Lecture	36	Lecture Based
Lecture	36	Lecture Based
Tutorial	24	Studio/Tutorial
Tutorial	24	Studio/Tutorial
Assignment Completion	90	No Description
Assignment Completion	90	No Description
Independent Study	37.5	No Description
Independent Study	37.5	No 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 Assessment	50%	Examination Weight	50%

Type	Description	% of total	Assessment Date
Course Work Breakdown
Project	Submission of a 6-page Conference paper:- Involves research, compilation, design of experiments, analysis of data on a research topic	25%	Week 30
In Class Test	Statistical problem based class test	25%	Week 29

Reassessment Requirement Type
Resit arrangements are explained by the following categories; 1 = A resit is available for all components of the module 2 = No resit is available for 100% continuous assessment module 3 = No resit is available for the continuous assessment component
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

Programme or List of Programmes

CAMIM	MEng in Mechanical & Manufacturing Eng
ECSA	Study Abroad (Engineering & Computing)
ECSAO	Study Abroad (Engineering & Computing)
GDSES	Grad Dip in Sustainable Energy Systems
MEPD	PhD
MEPM	MEng
MEPT	PhD-track
MMME	MEng in Mechanical and Manufacturing Eng
MMQB	Qualifier B for MEng. Mech & Manu Eng.
SMPEC	Single Module Programme (Eng & Comp)

Date of Last Revision

18-DEC-08

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