Inferential Statistics

Inferential Statistics is a branch of statistics that uses probability-based methods to draw conclusions about population parameters, including estimation and hypothesis testing, from data obtained from samples.

43.5K

Publications

5.1M

Citations

40.3K

Authors

7.1K

Institutions

Publications per year

2017–2026

5.3K

Authors

40.3K

  1. BE
    Bradley Efron

    Stanford University, United States

    80 publications · 30K citations

    59

    h-index

  2. NB
    N. Balakrishnan

    McMaster University, Canada

    207 publications · 11K citations

    53

    h-index

  3. RJ
    Raymond J. Carroll

    Texas A&M University, United States

    83 publications · 7K citations

    44

    h-index

  4. DB
    Donald B. Rubin

    Harvard University, United States

    61 publications · 42.3K citations

    42

    h-index

  5. ER
    Eric R. Ziegel

    Kyocera (United States), United States

    68 publications · 34.2K citations

    42

    h-index

1–5 of 40.3K

Venues

  1. Journal of the American Statistical Association

    3.8K publications · 572.5K citations

    317

    h-index

  2. Technometrics

    1.3K publications · 294.5K citations

    214

    h-index

  3. The Annals of Statistics

    1.7K publications · 220.4K citations

    206

    h-index

  4. Biometrika

    1.9K publications · 226.2K citations

    187

    h-index

  5. Biometrics

    1.1K publications · 211.2K citations

    171

    h-index

1–5