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Visualising nursing data using correspondence analysis
Peter Kokol1, Helena Blažun Vošner2, Danica Železnik3
1Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia.
Background:
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.
Aim:
To demonstrate the use of visualisation of big data in a technique called correspondence analysis.
Discussion:
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.
Conclusion:
Correspondence analysis supports the discovery of new knowledge. Implications for practice Knowledge obtained using correspondence analysis can be transferred immediately into practice or used to foster further research.
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