Statistical Summarization

Statistical Summarization is a data reduction technique that belongs to the class of methods aimed at reducing data volume by retaining summarized statistical measures, distinguished by its focus on computing and preserving aggregate metrics—such as mean, variance, frequency, or distributional properties—to represent the original dataset in a condensed form.

80

Publications

14.3K

Citations

197

Authors

97

Institutions

Publications per year

2017–2026

19

Authors

197

  1. RR
    Ronald R. Yager

    Iona College, United States

    4 publications · 504 citations

    4

    h-index

  2. RR
    Robert Rosenthal

    Harvard University Press, United States

    3 publications · 345 citations

    3

    h-index

  3. JA
    Jordan Anaya

    University of Virginia, United States

    2 publications · 65 citations

    2

    h-index

  4. LO
    Lyman Ott

    University of Florida, United States

    2 publications · 1.5K citations

    2

    h-index

  5. AS
    Arie Shoshani

    Lawrence Berkeley National Laboratory, United States

    2 publications · 366 citations

    2

    h-index

1–5 of 197

Venues

  1. Technometrics

    6 publications · 7.4K citations

    6

    h-index

  2. Psychological Bulletin

    4 publications · 617 citations

    4

    h-index

  3. Multimedia Tools and Applications

    3 publications · 116 citations

    3

    h-index

  4. Information Sciences

    2 publications · 473 citations

    2

    h-index

  5. Statistics in Medicine

    2 publications · 58 citations

    2

    h-index

1–5