Two-sample Hypothesis Test

A Two-Sample Hypothesis Test is a statistical procedure that belongs to the class of hypothesis testing methods and is distinguished by its purpose of comparing parameters or distributions from two independent samples to determine whether there is sufficient evidence to reject a null hypothesis regarding their equivalence.

521

Publications

43.6K

Citations

963

Authors

472

Institutions

Publications per year

2017–2026

88

Variants

Two-sample Test

Authors

963

  1. LJ
    Lee J. Bain

    Missouri University of Science and Technology, United States

    6 publications · 151 citations

    6

    h-index

  2. AG
    Arthur Gretton

    University College London, United Kingdom

    5 publications · 630 citations

    5

    h-index

  3. KA
    Kjell A. Doksum

    University of California, Berkeley, United States

    5 publications · 376 citations

    5

    h-index

  4. DA
    Douglas A. Wolfe

    The Ohio State University, United States

    4 publications · 163 citations

    4

    h-index

  5. BL
    B. L. van der Waerden

    University of Zurich, Switzerland

    4 publications · 243 citations

    4

    h-index

1–5 of 963

Venues

  1. Journal of the American Statistical Association

    36 publications · 2.5K citations

    24

    h-index

  2. Biometrika

    26 publications · 4.6K citations

    22

    h-index

  3. The Annals of Mathematical Statistics

    27 publications · 4.3K citations

    22

    h-index

  4. The Annals of Statistics

    20 publications · 2.3K citations

    17

    h-index

  5. Biometrics

    21 publications · 2K citations

    17

    h-index

1–5