This is an orthodox account of an old-fashioned approach. But note that
the mention of Gaussians is a complete red herring. The K-S test as
approached by Claudia is focusing on whether two distributions are
different, which is nothing to do with whether either is Gaussian.
Nick
[email protected]
hind sbihi
Claudia
I am not sure I fully understand your question.
However, for hypothesis testing, you need to set a critical value at
which
you accept or reject the null hypothesis. Let's say this critical value,
or
alpha is 0.05. Now, if p-value is less than 0.05 your reject the null
hypothesis (which states that your observed distribution follows a
Gaussian
distribution). Conversely, if p>0.05 then you accept the null hypothesis
and
consider that your data approximates a Gaussian distribution.
[email protected]
would someone guide me on how to interpret the output of a two-sided
kolmogorov-Smirnov test?
In order to conclude for the equality or not of the distributions, what
p-value I have to see? As you know, if I perform a test for the
equality of two distributions, I have three rows where the last one is
the combined K-S. My question is if I have to see only this last row
(p-value) in ordwer to drow a conclusion.
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