Kolmogorov-Smirnov test — one- and two-sample.

medium

Answer

$D\; = \;\operatorname{max}_{x}\; \mid F_{1}(x)\; - \;F_{2}(x)$
$Distribution-free, works for continuous data, sensitive to shifts in location, scale, or shape.$
$Weakness: less sensitive in the tails.$
$Use in drift detection (compare distribution today vs baseline).$

Check yourself — multiple choice

Only parametric
$D\; = \;\operatorname{max}\; \mid F_{1}\; - \;F_{2}$ |; distribution-free; sensitive to location/scale/shape; used for drift detection
Requires normality
Same as t-test

KS test: max CDF gap; distribution-free; foundation of drift detection.

#hypothesis-testing#non-parametric

215 interview questions in this topic.