Vision Zero Data:
The data used for this analysis driven from:
Calculation Mythology:
Summary: KS-test tests whether two samples are drawn from the same distribution. It returns two floats: the first is KS statistic, the second is two-tailed p-value. In terms of the Null hypothesis, if the K-S statistic is small or the p-value is high, then we cannot reject the hypothesis that the distributions of the two samples are the same. Applying to the Vision Zero case, since the p-value is just 1.1701245566351613e-37 which is far smaller than critical value 0.05, we reject the Null hypothesis that there is no statistical difference in the for the before and after the adoption of Vision Zero.
The scipy.stats KS test already tells us the significance and the p-value.
Remember: the Null hypothesis is rejected if
The p-value returned by the k-s test has the same interpretation as other p-values. You reject the null hypothesis that the two samples were from the same distribution if the p-value is less than your significance level. You can find tables online for the conversion of the D statistic into a p-value if you are interested in the procedure.