If the hypothesis has been proven wrong or falsifiable, it is important because if something is proven wrong, then the opposing hypothesis must be true. Therefore, it leads to determining the correct find. Null-hypothesis testing answers the question of "how well the findings fit the possibility that chance factors alone might be responsible." !
