How to use ks test for 2 vectors of scores in python?

I am trying to figure out how to determine whether to reject or not the null hypothesis using ks-test.

1. In matlab there is a function named kstest2 decides if it should reject $H_0$. I want to use python scipy function ks_2samp but it returns the p-value and the $\alpha$, how can I determine if one should reject $H_0$ given those 2 parameters ?
2. If I have 2 vectors of scores per day, how can I use Matlab/python kstest2 to see if the are distributed the same?
3. Is there a clean way to change the scores vector to a continuous distributed vector?
• Simply compare the p-value to your significance level. If your p-value is lower than (or equal to) your significance level (your chosen type I error rate), you should reject the null hypothesis. – Glen_b Oct 2 '13 at 22:59
• @Glen_b do you mean if $\alpha > p-value$ reject $H_0$ ? Does $D statistic$ is the same as $alpha$ – 0x90 Oct 2 '13 at 23:01
• Yes and no. Or more strictly, since $\alpha$ is fixed (chosen by you prior to the test), the $\alpha$ is the thing being compared against, so it's the way around I initially stated. And if they happen to be equal you also reject. So I mean it as I said it in words before: if $\text{p-value}\leq\alpha$ you should reject $H_0$. No, $D$ is NOT $\alpha$. $D$ is something you calculate from the sample, while $\alpha$ is something you would normally choose before you even collect the sample and certainly before you look at it. en.wikipedia.org/wiki/Statistical_significance – Glen_b Oct 2 '13 at 23:05

1. Simply compare the p-value to your desired significance level. If your p-value is less than (or equal to) your significance level (your chosen type I error rate, $\alpha$), you should reject the null hypothesis. (You may need to brush up your understanding of how hypothesis testing works.)