I'm confused about the appropriate interpretation of p-values returned by the two-sample Kolmogorov-Smirnov test (ks.test) in R.
In slide 23 of this presentation about non-parametric two-sample tests, the author states that when analyzing the ks.test results:
ks.test(male, female) Two-sample Kolmogorov-Smirnov test data: male and female D = 0.8333, p-value = 0.02597
needs to be multiplied by 2 for a 2-tail test. Thus, P = 0.05194
Is that true?
If we used the original p = 0.02597, we would reject the hypothesis that the distributions similar, because p < 0.05, correct? Whereas if we multiply it by 2, the p would suggest that there is no difference between distributions, since p > 0.05?
What am I missing?