SKEWNESS_P
Updated 2024-02-13 19:42:30.867000
Syntax
SELECT [westclintech].[wct].[SKEWNESS_P] (
<@Known_x, float,>)
Description
Use the aggregate function SKEWNESS_P to calculate the skewness for an entire population. The SKEWNESS_P function is an implementation of the skewness as formulated by Abramowitz and Stegun in Handboook of Mathematical Functions, 26.1.15.
\gamma_1=\frac{\mu_3}{\mu_2^{3/2}}
Arguments
@Known_x
the values to be used in the calculation. @Known_x must be of a type float or of a type that implicitly converts to float.
Return Type
float
Remarks
If you want measure the skewness for a sample, then use the SKEWNESS_S function.
To calculate the population kurtosis use the KURTOSIS_P function.
To calculate the sample kurtosis use the KURTOSIS_S function.
Examples
SELECT wct.SKEWNESS_P(x) as SKEWNESS_P
FROM
(
SELECT 30000.0000216303
UNION ALL
SELECT 30000.0000565854
UNION ALL
SELECT 30000.000038137
UNION ALL
SELECT 30000.0000495983
UNION ALL
SELECT 30000.0000185861
UNION ALL
SELECT 30000.0000863479
UNION ALL
SELECT 30000.0000776366
UNION ALL
SELECT 30000.0000637985
UNION ALL
SELECT 30000.0000939786
UNION ALL
SELECT 30000.000031191
UNION ALL
SELECT 30000.0000550457
UNION ALL
SELECT 30000.0000207558
UNION ALL
SELECT 30000.0000805531
UNION ALL
SELECT 30000.0000241287
) n(x);
This produces the following result
{"columns":[{"field":"SKEWNESS_P","headerClass":"ag-right-aligned-header","cellClass":"ag-right-aligned-cell"}],"rows":[{"SKEWNESS_P":"0.204132079810574"}]}
In this example, we generate 100 random numbers form the standard normal distribution using the wct.SeriesFloat function and calculate the population skewness.
SELECT wct.SKEWNESS_P(k.SeriesValue) as SKEWNESS_P
FROM wctMath.wct.SeriesFloat(0, 1, NULL, 100, 'N') k;
This produces the following result (your results will be different).
{"columns":[{"field":"SKEWNESS_P","headerClass":"ag-right-aligned-header","cellClass":"ag-right-aligned-cell"}],"rows":[{"SKEWNESS_P":"-0.143810928339362"}]}