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kurtosis
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The kurtosis function determines the peakedness or flatness of the distribution
curve defined by a set of data points. A normal distribution has a kurtosis of 0.
A negative kurtosis value describes a distribution that is flatter than normal (platykurtic);
a positive kurtosis value describes a distribution more peaked than normal (leptokurtic).
When to use The kurtosis function is used to compute the peakedness or flatness of the distribution curve defined by a set of data points.
Returns a number corresponding to the the peakedness or flatness of the distribution
curve defined by a set of data points. Any arguments that cannot be evaluated as numbers
are ignored in the calculation of kurtosis. Also, if there are less than four data points
or if the sample standard deviation is zero, the kurtosis function returns an error
value.
Here are a number of links to Lambda coding examples which contain this instruction in various use cases.
This example defines the data points in the argument list. The
kurtosis function returns the peakedness or flatness of the distribution curve
as defined by the data points.
Here are the links to the data types of the function arguments. Here are also a number of links to functions having arguments with any of these data types.
You can always talk with the AIS at aiserver.sourceforge.net.
Name
Description
AIS Types num1 ... Any number of values Number
Returns:
Examples
Argument Types
Number
Integer
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