Variance Visualization

Variance Visualization is a visual representation method that specifically encodes the statistical variance of multivariate data or model outputs to convey the dispersion and reliability of values within a given dataset or predictive model.

4

Publications

158

Citations

14

Authors

6

Institutions

Publications per year

2017–2026

0

Authors

14

  1. JW
    John W. Tukey

    Princeton University, United States

    1 publications · 55 citations

    1

    h-index

  2. QW
    Qiu Wang

    University of Chinese Academy of Sciences, China

    1 publications · 48 citations

    1

    h-index

  3. JE
    John E. Johnson

    Scripps Research Institute, United States

    1 publications · 48 citations

    1

    h-index

  4. FM
    Frederick Mosteller

    Harvard University Press, United States

    1 publications · 55 citations

    1

    h-index

  5. KR
    K. R. Gabriel

    University of Rochester, United States

    1 publications · 39 citations

    1

    h-index

1–5 of 14

Venues

  1. The American Statistician

    1 publications · 16 citations

    1

    h-index

  2. Biometrics

    1 publications · 39 citations

    1

    h-index

  3. Journal of Structural Biology

    1 publications · 48 citations

    1

    h-index

  4. 1

    h-index

1–4