Fair Statistical Communication in HCI
By Pierre Dragicevic. 2016
346 citations recorded by the source corpus.
Statistics are tools to help end users accomplish their task. In research, to be qualified as usable, statistical tools should help researchers advance scientific knowledge by supporting and promoting the effective communication of research findings. Yet areas such as human-computer interaction (HCI) have adopted tools — i.e., p-values and dichotomous testing procedures — that have proven to be poor at supporting these tasks. The abusive use of these procedures has been severely criticized in a range of disciplines for several decades, suggesting that tools should be blamed, not end users. This chapter explains in a non-technical manner why it would be beneficial for HCI to switch to an estimation approach, i.e., reporting informative charts with effect sizes and interval estimates, and offering nuanced interpretations of our results. Advice is offered on how to communicate our empirical results in a clear, accurate, and transparent way without using any tests or p-values.
Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology
View Paper: https://www.semanticscholar.org/paper/4d31c31ea8081305952f48202e5485ab763c09b7
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In Artificial Intelligence
In Computer Vision and Pattern Recognition
In Experimental and Cognitive Psychology
Citations in the corpus
- Are Explanations Helpful? A Comparative Study of the Effects of Explanations in AI-Assisted Decision-Making (2021, methodology): “To avoid multiple comparison problems and control false discovery, we conducted our analyses using the interval estimate method [21, 25].”