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Hypothesis Testing (Wilcoxon Signed-Rank Test » Paired Samples) (G Dataflow)

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Last Modified: June 25, 2019

Tests hypotheses about the mean of two populations whose distributions are continuous and symmetric but not necessarily normal.

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sample set x

Sampled data from population x.

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sample set y

Sampled data from population y.

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delta

Hypothetical mean of the differences between sample set x and sample set y.

Default: 0

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significance level

Probability that this node incorrectly rejects a true null hypothesis.

Default: 0.05

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error in

Error conditions that occur before this node runs.

The node responds to this input according to standard error behavior.

Standard Error Behavior

Many nodes provide an error in input and an error out output so that the node can respond to and communicate errors that occur while code is running. The value of error in specifies whether an error occurred before the node runs. Most nodes respond to values of error in in a standard, predictable way.

error in does not contain an error error in contains an error
If no error occurred before the node runs, the node begins execution normally.

If no error occurs while the node runs, it returns no error. If an error does occur while the node runs, it returns that error information as error out.

If an error occurred before the node runs, the node does not execute. Instead, it returns the error in value as error out.

Default: No error

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alternative hypothesis

Hypothesis to accept if this node rejects the null hypothesis that the two variable populations have a common mean.

Name Value Description
mean(x - y) != delta 0 The mean of the differences between population x and population y is not equal to delta.
mean(x - y) > delta 1 The mean of the differences between population x and population y is greater than delta.
mean(x - y) < delta -1 The mean of the differences between population x and population y is less than delta.

Default: mean(x - y) != delta

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null hypothesis rejected?

A Boolean that indicates whether this node rejects the null hypothesis.

True p value is less than or equal to significance level. This node rejects the null hypothesis and accepts the alternative hypothesis.
False p value is greater than significance level. This node accepts the null hypothesis and rejects the alternative hypothesis.
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p value

Smallest significance level that leads to rejection of the null hypothesis based on the sample sets.

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error out

Error information.

The node produces this output according to standard error behavior.

Standard Error Behavior

Many nodes provide an error in input and an error out output so that the node can respond to and communicate errors that occur while code is running. The value of error in specifies whether an error occurred before the node runs. Most nodes respond to values of error in in a standard, predictable way.

error in does not contain an error error in contains an error
If no error occurred before the node runs, the node begins execution normally.

If no error occurs while the node runs, it returns no error. If an error does occur while the node runs, it returns that error information as error out.

If an error occurred before the node runs, the node does not execute. Instead, it returns the error in value as error out.

Where This Node Can Run:

Desktop OS: Windows

FPGA: Not supported

Web Server: Not supported in VIs that run in a web application

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