## S_TEST

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. 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."

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.

### Calling Sequence

Result = S_TEST( X, Y )

### 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.

### Example

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.