KSTEST2

Updated 2023-10-26 14:13:12.697000

Syntax

SELECT [westclintech].[wct].[KSTEST2] (
  <@sid, nvarchar(4000),> 
 ,<@x, float,> 
 ,<@statistic, nvarchar(4000),>)

Description

Use the aggregate function KSTEST2 to perform the two-sample Kolmogorov-Smirnov test to compare the distributions of the values in two samples. KSTEST2 produces the test statistic (k) and the p-value (p) which can be used to ascertain if the two samples are from the same continuous distribution.

Arguments

@statistic

identifies the return value as either the Kolmogorov-Smirnov statistic (k) or the p-value (p).

@x

the sample value. @x is an expression of type float or of a type that can be implicitly converted to float.

@sid

the sample identifier. @sid indentifies which of the two samples @ x belongs to.

Return Type

float

Remarks

If @x is null then @x is not included in the aggregate.

There must exactly 2 @sid within a GROUP.

@statistic must be invariant for the GROUP.

KSTEST2 is an aggregate function and follows the same conventions as all other aggregate functions in SQL Server.

To evaluate one sample against a continuous distribution function, use KSTEST.

Examples

In this example, we compare a sample of test scores for men and women.

SELECT wct.KSTEST2(s, x, 'p') as p_value,
       wct.KSTEST2(s, x, 'k') as k_observed
FROM
(
    SELECT 'Men',
           117
    UNION ALL
    SELECT 'Men',
           106
    UNION ALL
    SELECT 'Men',
           105
    UNION ALL
    SELECT 'Men',
           112
    UNION ALL
    SELECT 'Men',
           108
    UNION ALL
    SELECT 'Men',
           115
    UNION ALL
    SELECT 'Men',
           97
    UNION ALL
    SELECT 'Men',
           112
    UNION ALL
    SELECT 'Men',
           110
    UNION ALL
    SELECT 'Women',
           131
    UNION ALL
    SELECT 'Women',
           107
    UNION ALL
    SELECT 'Women',
           110
    UNION ALL
    SELECT 'Women',
           108
    UNION ALL
    SELECT 'Women',
           100
    UNION ALL
    SELECT 'Women',
           74
    UNION ALL
    SELECT 'Women',
           89
    UNION ALL
    SELECT 'Women',
           115
    UNION ALL
    SELECT 'Women',
           85
    UNION ALL
    SELECT 'Women',
           94
    UNION ALL
    SELECT 'Women',
           110
    UNION ALL
    SELECT 'Women',
           80
    UNION ALL
    SELECT 'Women',
           103
    UNION ALL
    SELECT 'Women',
           122
) n(s, x);

This produces the following result

{"columns":[{"field":"p_value","headerClass":"ag-right-aligned-header","cellClass":"ag-right-aligned-cell"},{"field":"k_observed","headerClass":"ag-right-aligned-header","cellClass":"ag-right-aligned-cell"}],"rows":[{"p_value":"0.297578744560361","k_observed":"0.388888888888889"}]}