Two-sample Kolmogorov-Smirnov test

[bradyj7]

Hello,

Hello,

I have recorded some discrete data with an unspecified distribution.

I have generated some discrete data from a model.

I'm looking to check to see if the generated data has the same distribution as the real data.

If the data was continious, I would use a Q-Q plot and a striaght line would indicate that it is true.

As the data is discrete, I need another test.

Can you use a two-sample Kolmogorov-Smirnov test to test the hypothesis that the two samples come from the same distribution?

Here is a link to the test http://www.mathworks.co.uk/help/stats/kstest2.html

Kind regards

J

 

[mmwave]

enny

Hello Jenny,

Thank you for reaching out regarding your data analysis. It sounds like you are on the right track in using a two-sample Kolmogorov-Smirnov test to compare the distribution of your real data and the data generated from your model.

The two-sample Kolmogorov-Smirnov test is a non-parametric test that can be used to compare two samples and determine if they come from the same distribution. It is suitable for both continuous and discrete data.

To perform this test, you will need to have at least 20 data points in each sample and the data should be independent. The test will produce a p-value, which can help you determine if there is a significant difference between the two distributions. A low p-value (typically less than 0.05) would indicate that the two distributions are significantly different, while a high p-value would suggest that they are similar.

I hope this helps with your analysis. Best of luck with your research!