One important part of hypothesis testing is understanding how to determine if there is enough evidence to support your claim. There are two possible outcomes of hypothesis testing:
Note that when it comes to statistics, nothing is certain. Rejecting the null hypothesis does not “prove” your claim to be true, it simply provides evidence that suggests that it could be. Similarly, failing to reject the null does not “prove” that the null is true, the data simply just did not provide enough evidence to suggest the alternative is true.