Kolmogorov-Smirnov Test
Summary:
The Kolmogorov-Smirnov test (KS-test) tries to determine if two datasets differ significantly. The KS-test has the advantage of making no assumption about the distribution of data. (Technically speaking it is non-parametric and distribution free.) Note however, that this generality comes at some cost: other tests (for example Student's t-test) may be more sensitive if the data meet the requirements of the test. In addition to calculating the D statistic, this page will report if the data seem normal or lognormal. (If it is silent, assume normal data at your own risk!) It will enable you to view the data graphically which can help you understand how the data is distributed.
The Kolmogorov-Smirnov test (KS-test) tries to determine if two datasets differ significantly. The KS-test has the advantage of making no assumption about the distribution of data. (Technically speaking it is non-parametric and distribution free.) Note however, that this generality comes at some cost: other tests (for example Student's t-test) may be more sensitive if the data meet the requirements of the test. In addition to calculating the D statistic, this page will report if the data seem normal or lognormal. (If it is silent, assume normal data at your own risk!) It will enable you to view the data graphically which can help you understand how the data is distributed.
In English:
Comparing two data sets, it draws plots to show the difference.
Link:
No comments:
Post a Comment