Hub
Pricing About
NodeNode / Manipulator

Friedman Test

KNIME LabsStatistics
Drag & drop
Like

The Friedman test is used to detect any difference between subjects under test measured variously multiple times. More precisely, this non-parametric test states whether there is a significant difference in the location parameters of k statistical samples (>= 3, columns candidates , treatments , subject ), measured n times ( rows , blocks , participants , measures ), or not. The data in each row is ranked, based on which a resulting test statistic Q is calculated.

If n > 15 or k > 4, the test statistic Q can be approximated to be Χ 2 distributed. With the given significance level α, a corresponding p -value (null hypothesis H 0 : there is no difference of the location parameters in the samples, alternative hypothesis H A : the samples in the columns have different location parameters) can be given.

Please refer also to the Wikipedia description of the Friedman Test .

Node details

Input ports
  1. Type: Table
    Input data
    The table from which to test samples
Output ports
  1. Type: Table
    Evaluation
    Friedman test evaluation

Extension

The Friedman Test node is part of this extension:

  1. Go to item

Related workflows & nodes

  1. Go to item
  2. Go to item
  3. Go to item

KNIME
Open for Innovation

KNIME AG
Talacker 50
8001 Zurich, Switzerland
  • Software
  • Getting started
  • Documentation
  • Courses + Certification
  • Solutions
  • KNIME Hub
  • KNIME Forum
  • Blog
  • Events
  • Partner
  • Developers
  • KNIME Home
  • Careers
  • Contact us
Download KNIME Analytics Platform Read more about KNIME Business Hub
© 2025 KNIME AG. All rights reserved.
  • Trademarks
  • Imprint
  • Privacy
  • Terms & Conditions
  • Data Processing Agreement
  • Credits