Some Prior(s) Experience Necessary: Templates for Getting Started With Bayesian Analysis

Telemedicine & Remote Patient MonitoringComputational Methods in HCIUniversity Professors & ResearchersData Scientists & AnalystsHCI Researchers

Bayesian statistical analysis has gained attention in recent years, including in HCI. The Bayesian approach has several advantages over traditional statistics, including producing results with more intuitive interpretations. Despite growing interest, few papers in CHI use Bayesian analysis. Existing tools to learn Bayesian statistics require significant time investment, making it difficult to casually explore Bayesian methods. Here, we present a tool that lowers the barrier to exploration: a set of R code templates that guide Bayesian novices through their first analysis. The templates are tailored to CHI, supporting analyses found to be most common in recent CHI papers. In a user study, we found that the templates were easy to understand and use. However, we found that participants without a statistical background were not confident in their use. Together our contributions provide a concise analysis tool and empirical results for understanding and addressing barriers to using Bayesian analysis in HCI.

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https://hci.top/en/papers/chi/6341/2019

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Source
CHI
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Year
2019
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4 authors
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Subtopics
Telemedicine & Remote Patient Monitoring, Computational Methods in HCI
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Professions
University Professors & Researchers, Data Scientists & Analysts, HCI Researchers
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Abstract only
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