Shapiro-Wilk Test

The Shapiro-Wilk test tests if a sample comes from a normally distributed population. The test is biased by sample size, so it may yield statistically significant results for any large sample.

This node is applicable for 3 to 5000 samples, but a bias may begin to occur with more than 50 samples.

More information can be found at Shapiro–Wilk test on Wikipedia.

Hypotheses:
H₀: sample comes from a normally distributed population.
H_A: sample does not originate from a normally distributed population.

Options

Significance level α: Significance level at which the null hypothesis can be rejected, 0 < α < 1.
Test Columns: The columns to test.
Use Shapiro-Francia for leptokurtic samples: Checks if the samples are leptokurtic, and if so uses Shapiro-Francia. Otherwise, falls back to Shapiro-Wilk.

Input Ports

: Input table with one or more numerical columns.

Output Ports

: Output table with the Shapiro-Wilk test statistic, p-Value, and acceptance/rejection of H₀.

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Installation

To use this node in KNIME, install the extension KNIME Statistics Nodes (Labs) from the below update site following our NodePit Product and Node Installation Guide:

v5.3

A zipped version of the software site can be downloaded here.

Plugin provider: KNIME AG, Zurich, Switzerland

Plugin version: 5.3.0.v202312081535

On NodePit since: 2024-07-09

Last update: 2024-11-20

KNIME versions: Since v3.7

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