Module Information

Module Identifier
PGM4310
Module Title
Quantitative Data Collection and Analysis
Academic Year
2017/2018
Co-ordinator
Semester
Semester 1
Also available in

Course Delivery

 

Assessment

Assessment Type Assessment length / details Proportion
Semester Assessment Quantitative Research Critique  40%
Semester Assessment Quantitative Research Report  60%
Supplementary Assessment Quantitative Research Critique  - resubmission of failed component using a different set of data from original  40%
Supplementary Assessment 2,000 word  resubmission of failed component using a different set of data from original submission  60%

Learning Outcomes

On successful completion of this module students should be able to:

Demonstrate an ability to conduct small and large scale survey projects
Collect quantitative data
Demonstrate an ability to manage research data, and use IT in such data management
Conduct research in a manner which is consistent with professional practice
Analyse large scale data sets

Brief description

This module is designed to be an integral component of the RT courses which the University has introduced in order to meet the joint funding Research Councils statement on Research Training. Through this module Masters and PhD students will gain a broad knowledge of a range of transferable skills which they can apply in a variety of research contexts.

Aims

The course is designed to give students a grounding in the basic principles of quantitative research methodology. It will include an analysis of the principles of quantitative research data and data analysis. The module will introduce students to the basic tenhniques of analysis, presentation and description of statistics.

Content

Statistical techniques and statistical packages including:
  • T-tests
  • Correlation
  • Analysis of Variance
  • Data entry, graphs, summary statistics
  • Anova

Module Skills

Skills Type Skills details
Application of Number This module will introduce students to the use, interpretation and presentation of statistical techniques, including statistical inference, measures of association and multivariate techniques.
Communication The module develops written communications skills via the coursework. Students will be expected to submit their work in word-processed format and the presentation of work should reflect effective expression of ideas and good use of language skills in order to ensure clarity and coherence.
Improving own Learning and Performance The whole module has an emphasis on providing students with a range of research skills to enable them to manage their own career development.
Information Technology One element of the module will introduce students to the uses of appropriate computer packages in the storage and analysis of different types of research material.
Personal Development and Career planning The module is explicitly designed to give students an appreciation of a broad range of research skills, which they will be able to utilise for career purposes beyond the particular skills they require for their own individual research topics.
Problem solving One explicit aim of the module is to develop the ability of students to undertake independent research projects, and a large element of the students’ learning will be directed to this end. Students will also be required to submit independent work which is linked to their own particular research topic, and to their ability to collect and analyse data.
Research skills Students will be partly assessed through a range of written material in which they will be expected to appropriately set out a range of research strategies.
Subject Specific Skills It is expected that the quantitative skills will be transferable to the student’s own research project.
Team work Team-working skills will be covered in the module in terms of the skills needed to conduct and administer group research. In this sense the research cycle will be used to impart team-working skills, from the initial formulation of research problems through to the implementation of research, the analysis of the data, and the dissemination of results.

Notes

This module is at CQFW Level 7