Table Of Contents

Measures of Spread (Skewness and Kurtosis) (G Dataflow)

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    Last Modified: March 15, 2017

    Computes the skewness and kurtosis of a sequence. Skewness is a measurement of symmetry. Kurtosis is the peak measurement of a distribution.

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    x

    The input sequence.

    If x is empty, this node sets skewness and kurtosis to NaN.

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    weighting

    Weighting mode that this node uses to compute the input sequence.

    Name Description
    Sample

    The input sequence is a random sample taken from a population.

    Population

    The input sequence is a complete population.

    Default: Sample

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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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    skewness

    Symmetrical measurement of the input sequence.

    Understanding the Value of skewness

    A negative value of skewness indicates that the left side of the probability density function is longer than the right side. The following image shows negative skewness.

    A positive value of skewness indicates that the right side of the probability density function is longer than the right side. The following image shows positive skewness.

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    kurtosis

    Peak measurement of the input sequence.

    Understanding the Value of kurtosis

    When determining kurtosis, normal distribution has a kurtosis value of 3. A kurtosis value of less than 3 indicates a flatter distribution than normal. A kurtosis value of greater than 3 indicates a sharper distribution than normal. The following figure shows three distributions with kurtosis values of 6, 3, 1.8.

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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: This product does not support FPGA devices


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