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Module Specifications

Archived Version 2012 - 2013

Module Title Research Practice & Methodology
Module Code MM533
School School of Mechanical and Manufacturing Engineering

Online Module Resources

Module Co-ordinatorDr Joseph StokesOffice NumberS381
NFQ level 9 Credit Rating 7.5
Pre-requisite None
Co-requisite None
Compatibles None
Incompatibles None
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
Reassessment Requirement
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
Unavailable
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
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BSSAStudy Abroad (DCU Business School)
BSSAOStudy Abroad (DCU Business School)
CAMCGCert CA Mechanical & Manufacturing Eng
CAMGGDip C.A. Mechanical & Manufacturing Eng
CAMMMSc. C.A. Mechanical & Manufacturing Eng
CAMVM.Eng. Mechanical & Manufacturing Eng
CAPDPhD
CAPMMSc
CAPTPhD-track
DRHECDRHEA Engineering and Computing
ECSAStudy Abroad (Engineering & Computing)
ECSAOStudy Abroad (Engineering & Computing)
EEPDPhD
EEPMMEng
EEPTPhD-track
HMSAStudy Abroad (Humanities & Soc Science)
HMSAOStudy Abroad (Humanities & Soc Science)
MEPDPhD
MEPMMEng
MEPTPhD-track
MEVMEng in Mechatronic Engineering
SHSAStudy Abroad (Science & Health)
SHSAOStudy Abroad (Science & Health)
SMPECSingle Module Programme (Eng & Comp)
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