Statistical Inference

Statistical Inference is the branch of statistics that uses probabilistic models and observed sample data to draw generalizable conclusions about unknown properties of underlying populations or data-generating mechanisms, thereby enabling estimation, prediction, and hypothesis assessment with quantified uncertainty.

51.3K

Publications

6M

Citations

50.5K

Authors

7.9K

Institutions

Publications per year

2017–2026

7.7K

Authors

50.5K

  1. BE
    Bradley Efron

    Stanford University, United States

    93 publications · 31.9K citations

    66

    h-index

  2. ER
    Eric R. Ziegel

    Kyocera (United States), United States

    86 publications · 29.5K citations

    52

    h-index

  3. AG
    Andrew Gelman

    Columbia University, United States

    89 publications · 39.3K citations

    51

    h-index

  4. RJ
    Raymond J. Carroll

    Texas A&M University, United States

    100 publications · 9K citations

    51

    h-index

  5. VC
    Victor Chernozhukov

    Massachusetts Institute of Technology, United States

    93 publications · 13.7K citations

    47

    h-index

1–5 of 50.5K

Venues

  1. Journal of the American Statistical Association

    3.8K publications · 624.6K citations

    338

    h-index

  2. Technometrics

    1.3K publications · 315K citations

    227

    h-index

  3. The Annals of Statistics

    1.9K publications · 253.9K citations

    225

    h-index

  4. Biometrika

    1.7K publications · 193.4K citations

    182

    h-index

  5. Biometrics

    987 publications · 197.1K citations

    167

    h-index

1–5