Evidence & Practice
Visualising nursing data using correspondence analysis
Peter Kokol Professor, Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia
Helena Blažun Vošner Head, Faculty of Health Sciences, Center for International Cooperation, University of Maribor
Danica Železnik Dean, University College of Health Sciences, Slovenj Gradec, Slovenia
Digitally stored, large healthcare datasets enable nurses to use ‘big data’ techniques and tools in nursing research. Big data is complex and multi-dimensional, so visualisation may be a preferable approach to analyse and understand it.
To demonstrate the use of visualisation of big data in a technique called correspondence analysis.
In the authors’ study, relations among data in a nursing dataset were shown visually in graphs using correspondence analysis. The case presented demonstrates that correspondence analysis is easy to use, shows relations between data visually in a form that is simple to interpret, and can reveal hidden associations between data.
Correspondence analysis supports the discovery of new knowledge.
Knowledge obtained using correspondence analysis can be transferred immediately into practice or used to foster further research.
Nurse Researcher. doi: 10.7748/nr.2016.e1441Correspondence
This article has been subject to double-blind review and has been checked for plagiarism using automated software
Received: 25 October 2015
Accepted: 17 March 2016
Published online: 04 August 2016
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