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Shapiro-Wilk Test

KNIME Statistic Nodes (Labs) version 4.3.0.v202011191636 by KNIME AG, Zurich, Switzerland

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.
HA: 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

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Input table with one or more numerical columns.

Output Ports

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

Best Friends (Incoming)

Best Friends (Outgoing)

Workflows

Installation

To use this node in KNIME, install KNIME Statistics Nodes (Labs) from the following update site:

KNIME 4.3

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

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