KURT

Calculates the kurtosis of a dataset, which describes the shape, and in particular the "peakedness" of that dataset.

Sample Usage

KURT(1,2,3,4,5,6,7,8,9,10)

KURT(A2:A100)

Syntax

KURT(value1, [value2, ...])

  • value1 - The first value or range of the dataset.

  • value2, ... - Additional values or ranges to include in the dataset.

Notes

  • Although KURT is specified as taking a maximum of 30 arguments, Google Sheets supports an arbitrary number of arguments for this function.

  • If the total number of values supplied as value arguments is not at least two, KURT will return the #DIV/0! error.

  • Any text encountered in the value arguments will be ignored.

  • Positive kurtosis indicates a more "peaked" distribution in the dataset, while negative kurtosis indicates a flatter distribution.

See Also

VARPA: Calculates the variance based on an entire population, setting text to the value `0`.

VARP: Calculates the variance based on an entire population.

VARA: Calculates the variance based on a sample, setting text to the value `0`.

VAR: Calculates the variance based on a sample.

STDEVPA: Calculates the standard deviation based on an entire population, setting text to the value `0`.

STDEVP: Calculates the standard deviation based on an entire population.

STDEVA: Calculates the standard deviation based on a sample, setting text to the value `0`.

SKEW: Calculates the skewness of a dataset, which describes the symmetry of that dataset about the mean.

DVARP: Returns the variance of an entire population selected from a database table-like array or range using a SQL-like query.

DVAR: Returns the variance of a population sample selected from a database table-like array or range using a SQL-like query.

DSTDEVP: Returns the standard deviation of an entire population selected from a database table-like array or range using a SQL-like query.

DSTDEV: Returns the standard deviation of a population sample selected from a database table-like array or range using a SQL-like query.

DEVSQ: Calculates the sum of squares of deviations based on a sample.

AVEDEV: Calculates the average of the magnitudes of deviations of data from a dataset's mean.

Examples

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