How Visualizing Inferential Uncertainty Can Mislead Readers About Treatment Effects in Scientific Results

    CHI '20: CHI Conference on Human Factors in Computing Systems Honolulu HI USA April, 2020, pp. 1-12, 2020.

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    Abstract:

    When presenting visualizations of experimental results, scientists often choose to display either inferential uncertainty (e.g., uncertainty in the estimate of a population mean) or outcome uncertainty (e.g., variation of outcomes around that mean) about their estimates. How does this choice impact readers' beliefs about the size of treat...More

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