Krishna Subramanian
ABSTRACT
To promote the practice of sound statistical analysis in HCI, we introduce VisiStat, a tool that allows users to perform statistical analysis by interacting with visualizations. It guides users to select the appropriate statistical analysis tasks based on the research questions they want to answer. By collocating statistical analysis results with appropriate visualizations, users are made aware of data-specific knowledge, which consequently improves their understanding of data and reduces common statistical analysis mistakes. In our user study, VisiStat helped users to answer 90% of the research questions they posed. On average, the users performed four statistical analysis tasks beyond their prior experience.
Supplemental Material
Available for Download
Zip file containing a PDF of the Accompanying Poster
- P. Cairns. HCI... Not As It Should Be: Inferential Statistics in HCI Research. In BCS-HCI '07, 195--201. Google Scholar
Digital Library
- S. Kandel, A. Paepcke, J. Hellerstein, and J. Heer. Wrangler: Interactive Visual Specification of Data Transformation Scripts. In CHI '11, 3363--3372. Google ScholarDigital Library
- J. Lazar, J. H. Feng, and H. Hochheiser. Research Methods in Human-Computer Interaction. Wiley Publishing, 2010. Google ScholarDigital Library
- H. C. Purchase. Experimental human-computer interaction: a practical guide with visual examples. Cambridge University Press, 2012. Google ScholarDigital Library
- J. M. Rzeszotarski and A. Kittur. TouchViz: (Multi)Touching Multivariate Data. In CHI EA '13, 1779--1784. Google ScholarDigital Library
- J. O. Wobbrock. Practical statistics for human-computer interaction. In Annual Workshop of the HCI Consortium (HCIC '11).Google Scholar
Index Terms
- VisiStat: visualization-driven, interactive statistical analysis
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