The S_TEST function tests the hypothesis that two sample populations *X* and *Y* have the same mean of distribution against the hypothesis that they differ.

This routine is written in the IDL language. Its source code can be found in the file s_test.pro in the lib subdirectory of the IDL distribution.

## Examples

; Define two n-element sample populations:

X = [47, 56, 54, 49, 36, 48, 51, 38, 61, 49, 56, 52]

Y = [71, 63, 45, 64, 50, 55, 42, 46, 53, 57, 75, 60]

; Test the hypothesis that the two sample populations have the same

; mean of distribution against the hypothesis that they differ at

; the 0.05 significance level:

PRINT, S_TEST(X, Y, ZDIFF = zdiff)

IDL prints:

[9.00000, 0.0729981]

The computed probability (0.0729981) is greater than the 0.05 significance level and therefore we do not reject the hypothesis that *X* and *Y* have the same mean of distribution.

## Syntax

*Result* = S_TEST( *X*, *Y* [, ZDIFF=*variable*] )

## Return Value

The result is a two-element vector containing the maximum number of signed differences between corresponding pairs of *xi* and *yi* and its one-tailed significance. This type of test is often referred to as the “Sign Test.”

## Arguments

### X

An *n*-element integer, single-, or double-precision floating-point vector.

### Y

An *n*-element integer, single-, or double-precision floating-point vector.

## Keywords

### ZDIFF

Set this keyword to a named variable that will contain the number of differences between corresponding pairs of *xi* and *yi* resulting in zero. Paired data resulting in a difference of zero are excluded from the ranking and the sample size is correspondingly reduced.

## Version History

4.0 |
Introduced |

## See Also

FV_TEST, KW_TEST, MD_TEST, RS_TEST, TM_TEST