SKEW

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

Sample Usage

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

SKEW(A2:A100)

Syntax

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

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

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

Notes

• Although SKEW 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, SKEW will return the #DIV/0! error.

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

• Positive skewness indicates a longer tail extending in the positive direction, to the right of the mean, while negative skewness indicates a longer tail in the negative direction, to the left. Skewness nearer to zero indicates more symmetrical distributions.

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`.

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

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.