Module: Research Practice & Methodology

Latest Module Specifications

Current Academic Year 2025 - 2026

Module Title	Research Practice & Methodology
Module Code	MEC1057 (ITS: MM533)
Faculty	Mechanical & Manufacturing Eng	School	Engineering & Computing
NFQ level	9	Credit Rating	7.5

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. 1D649F98-7E3D-0001-F4E2-F5309602FCB0

*Type*	*Hours*	*Description*
Workload	Full time hours per semester
Lecture	36	Lecture Based
Tutorial	24	Studio/Tutorial
Assignment Completion	90	No Description
Independent Study	37.5	No Description
Lecture	36	Lecture Based
Tutorial	24	Studio/Tutorial
Assignment Completion	90	No Description
Independent Study	37.5	No Description
Total Workload: 375

Section Breakdown
CRN	21344	Part of Term	Semester 2
Coursework	0%	Examination Weight	0%
Grade Scale	40PASS	Pass Both Elements	Y
Resit Category	RC1	Best Mark	N
Module Co-ordinator	Joseph Stokes	Module Teacher

Type	Description	% of total	Assessment Date
Assessment 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
Formal Examination	End-of-Semester Final Examination	50%	End-of-Semester

Reassessment Requirement Type
Resit arrangements are explained by the following categories; RC1: A resit is available for both^* components of the module. RC2: No resit is available for a 100% coursework module. RC3: No resit is available for the coursework component where there is a coursework and summative examination element. ^* ‘Both’ is used in the context of the module having a coursework/summative examination split; where the module is 100% coursework, there will also be a resit of the assessment

Pre-requisite	None
Co-requisite	None
Compatibles	None
Incompatibles	None

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

Indicative Reading List

Books:

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,

Articles:
None

Other Resources

None