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Combining details of the chi-square goodness-of-fit test with multivariate data visualization
|Kohlhammer, J.; Keim, D.A. ; European Association for Computer Graphics -EUROGRAPHICS-:|
EuroVAST 2010, First International Symposium on Visual Analytics Science and Technology : Held on June 8, 2010 in Bordeaux, France, co-located with the annual EuroVis 2010 Conference
Goslar: Eurographics Association, 2010
|International Symposium on Visual Analytics Science and Technology (EuroVAST) <1, 2010, Bordeaux>|
Symposium on Visualization (EuroVis) <12, 2010, Bordeaux>
|Fraunhofer IGD ()|
| visual analytic; statistic; multidimensional data visualization|
In this work, we combine KVMaps, a visualization technique presented in [May07] for the visualization of statistical aggregations in multivariate contingency tables, with the measures used for the statistical Chi-Square goodness-of-fit test. Goodness-of-fit tests are used to check whether a given distribution of values matches an expected distribution. A single test statistic is calculated to represent the deviation of the complete dataset. By visualizing the deviations for all entries in the contingency table, it is possible to identify the patterns in the distribution of data items, which contribute most to the overall deviation of the dataset. We present two use cases to illustrate how the information about the patterns can be used.