# Is it scientifically correct to derive conclusions unrelated to hypothesis from A/B test data

Consider a software A/B test with the hypothesis that "the addition of feature F is predicted to increase metric X".

At the end of the test, the data doesn't show any significant change in X, but it does show a significant increase in Y - something that wasn't expected or even considered at the beginning of the experiment.

At this point, is it scientifically valid to say that F increases Y, or should a new A/B test be designed and executed?

• "you still need to go back and do an experiment" - but why is this the case, if the data is clearly showing the effect on Y? – Jon Burgess Mar 28 '17 at 23:51