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.

Popular Predecessors

Popular Successors

Views

This node has no views

Workflows

Developers

You want to see the source code for this node? Click the following button and we’ll use our super-powers to find it for you.

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:

v5.4

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

Plugin provider: KNIME AG, Zurich, Switzerland

Plugin version: 5.4.0.v202407231410

On NodePit since: 2024-12-06

Last update: 2024-12-21

KNIME versions: Since v3.7

Deploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud or on-premises – with our brand new NodePit Runner.

Try NodePit Runner!