Methods, Metrics And Analytics
Research methods, quantitative methods; qualitative methods, web analytics, Social Network Analysis, data visualisation, data analysis, big data
|This Version is No Longer CurrentThe latest version of this module is available here
|Prerequisites for Module|
Aims of Module
The module provides students with an understanding of a range of research methods applicable to both academic enquiry and professional practice. Students will use a range of computational and non computional methods to gather, analyse and present data.
Learning Outcomes for Module
On completion of this module, students are expected to be able to:
||Demonstrate a critical understanding and awareness of a range of research methods and their application.|
||Work autonomously in the development of a research question and the identification of appropriate methods for data gathering and analysis.|
||Evaluate and apply data visualisation tools and techniques to present data in a form appropriate to the research context.|
||Develop a critical understanding of the legal and ethical considerations in the collection and management of data.|
Indicative Module Content
Research in both an academic and professional context. Data gathering - qualitative, quantitative and computational methods. Web analytics, social network analytics, understanding metrics. Programming for data gathering, analysis and visualisation. Social Network Analysis. Visualisation principles, tools and techniques.
|Indicative Student Workload|
|Full Time||Part Time|
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Mode of Delivery
The module is delivered via online exercises, workshops, industry speakers, case studies and lab tutorials.
||Learning Outcomes Assessed|
|Component 1 ||1,2,3,4|
Coursework - Students are required to develop a suitable research question, identify data sources and produce a report detailing the topic, the approach and presenting the resulting data in an appropriate and meaningful format.
|1.||DAWSON, C., 2009. Introduction to research methods: a practical guide for anyone undertaking a research project. 4th ed. Oxford: How to Books. ebook|
|2.||MAYER-SCHONBERGER, V. and CUKIER, K., 2013. Big data: a revolution that will transform how we live, work and think. London: John Murray.|
|3.||PRELL, C., 2012. Social network analysis: |
history, theory and methodology. Los Angeles: Sage.
|4.||TUFTE, E., 2001. The visual display of quantitative information. 2nd ed. Cheshire, Conn.: Graphics Press.|