KURTCalculates 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