Calculate the skewness of a distribution.

`SKEW.P(number1, [number2], [number3], â€¦)`

- number 1 - required argument that is a number
- number 2, ... - [OPTIONAL] argument that is a number

`=SKEW.P(B5:B15)`

The SKEW.P function in Sourcetable is used to calculate the skewness of a distribution. Skewness is the measure of the asymmetry of the probability distribution of a real-valued random variable. The skewness of a distribution can range from -1 to 1. A skewness of 0 implies that the distribution is symmetric. The SKEW.P function takes a range of cells containing numerical data and returns the skewness of the data set. For example, this calculates the skewness of the values in cells B5 to B15 and returns 0.7658 if there are 11 numeric values in the range and the count of values is the inverse of each other.

`=SKEW.P(C5:C15)`

If the data set has a negative skewness, the SKEW.P function will return a negative number. For example, this calculates the skewness of the values in cells C5 to C15 and returns -0.7658 if there are 11 numeric values in the range and the count of values is the inverse of each other.

`=SKEW.P(B5:B15)-SKEW.P(C5:C15)`

The SKEW.P function can also be used to compare the skewness of two different data sets. For example, this calculates the difference in skewness between the values in cells B5 to B15 and cells C5 to C15. If the difference is greater than 0, then the data set in cells B5 to B15 is more skewed than the data set in cells C5 to C15.

`=SKEW.P(D5:D15)`

The SKEW.P function can also be used to determine if a data set is symmetric or not. If the skewness is 0, then the data set is symmetric. For example, this calculates the skewness of the values in cells D5 to D15.

The SKEW.P function is used to measure the degree of asymmetry of a population's distribution around its mean. It takes a population as an argument and returns a value indicating the skewness of the data set.

- The SKEW.P function takes a range or reference as its first argument, and an optional second argument.
- The skewness of a distribution measures symmetry, and a positive result indicates a distribution that tails off to the right, and a negative result indicates a distribution that tails off to the left.

The SKEW.P function is a statistical function that calculates the skewness of a distribution. This function takes a population as its argument and returns a description of the degree of asymmetry of a distribution.

If there are fewer than three data points, the SKEW.P function will return the #DIV/0! error.

Skewness is a measure of the asymmetry of a distribution. Skewness can be positive, negative, or zero.

- Positive skewness occurs when the majority of the data is concentrated in the left tail of the distribution.
- Negative skewness occurs when the majority of the data is concentrated in the right tail of the distribution.
- Zero skewness occurs when the data is evenly distributed between the tails of the distribution.