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
```

the p-value

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?