# 2.13.1.9 kstest

## Brief Information

One sample Kolmogorov-Smirnov test for normality

## Command Line Usage

 

kstest irng:=col(2) 

## Variables

Display
Name
Variable
Name
I/O
and
Type
Default
Value
Description
Input irng

Input

Range

<active>

Specify the input data range

Statistics stat

Output

double

<unassigned>

Specify the mean of the normal distribution. If value is <auto>, Origin will calculate it automatically

Variance df

Output

double

<unassigned>

Specify the variance of the normal distribution. If value is <auto>, Origin will calculate it automatically

Statistics prob

Output

double

<unassigned>

The computed test statistics, D.

## Description

This function provides Kolmogorov-Smirnov test to compare the maximum distance between sample cumulative distribution function with the theoretical cumulative distribution function to determine whether the sample comes from a population of the theoretical distribution specified by user. Currently, Origin tests the normality only.

## Examples

1. Highlight and right-click a column, select Fill Column With: Normal Random Numbers to fill some data on the column.

2. Type kstest on the command window. The probability of null hypothesis can be seen from kstest.prob.

## Algorithm

For a given sample data $x_1,x_2,... ,x_n$, let $S_n(x_{(i)})$ and $F_0(x_{(i)})$) represent the sample cumulative distribution function and the theoretical (null) cumulative distribution function respectively at the point $x_{(i)}$ where $x_{(i)}$ is the ith smallest sample observation, the K-S test provides a test of the null hypotheses $H_0$: The data are a random sample of observations from the theoretical distribution specified by user. Currently, Origin tests the normality only.

To measure the difference between $S_n(x_{(i)}$ and $F_0(x_{(i)})$, K-S test compute the maximum absolute difference between the two cumulative distribution functions:  And then D will be used to compute the probability of null hypothesis.

Origin calls a NAG function, nag_1_sample_ks_test (g08cbc), to compute the statistics. Please refer to related NAG document, for more details on the algorithm.

## References

William H. Press, etc. 2002. Numerical Recipes in C++. Cambridge University Press.

## Related X-Functions

Keywords:variance