Comparing the effectiveness of visualizations of different data distributions
The effectiveness of a data visualization depends on several factors, such as the visual encoding of its elements, the analytical task it aims to support, the dimensionality of the data, and even the data distribution. In this work, we report an empirical evaluation of common data visualizations, focusing on how different data distributions affect their effectiveness and the level of confidence users have when answering questions related to certain analytical task types. The study allowed us to assess to what extent some data visualizations are more effective than others, regardless of data distribution. We conclude that data visualization creators and algorithms need to consider the data distribution when generating data visualizations. From the results, we also propose recommendations for choosing a visualization when dealing with data distribution issues.
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