Confidence Visualization

Confidence Visualization is a visualization technique that represents the degree of certainty or statistical confidence associated with data points, model predictions, or inferred relationships, distinguishing itself from other uncertainty visualization methods by focusing specifically on confidence intervals, confidence levels, or probabilistic bounds derived from sampling or inferential statistics.

24

Publications

1.6K

Citations

81

Authors

40

Institutions

Publications per year

2017–2026

10

Authors

81

  1. JC
    Jong Chul Ye

    Korea Advanced Institute of Science and Technology, South Korea

    1 publications · 36 citations

    1

    h-index

  2. AJ
    Alexander J. Karran

    HEC Montréal, Canada

    1 publications · 49 citations

    1

    h-index

  3. EK
    Eunyee Koh

    Adobe Systems (United States), United States

    1 publications · 60 citations

    1

    h-index

  4. JH
    Jessica Hullman

    University of Washington, United States

    1 publications · 69 citations

    1

    h-index

  5. DH
    David H. O’Connor

    University of Wisconsin–Madison, United States

    1 publications · 11 citations

    1

    h-index

1–5 of 81

Venues

  1. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 2 publications · 89 citations

    2

    h-index

  2. Statistics in Medicine

    1 publications · 662 citations

    1

    h-index

  3. Frontiers in Neuroscience

    1 publications · 49 citations

    1

    h-index

  4. 1

    h-index

  5. Teaching Statistics

    1 publications · 19 citations

    1

    h-index

1–5