Trick to remember when to reject null (p-values vs alpha) I teach introductory statistics to undergraduates and they are often confused with hypothesis testing. In particular, while the rule is

we reject the null hypothesis at significance level $\alpha$ when p value is less than $\alpha$

they many times interpret it the opposite. Say, if p value is 0.04, they say "we reject at 1% but not at 5%".
On one level, it is about the deeper understanding, which might be my fault as a teacher. But on another level (given that we are not always engaging with the deeper side of things), perhaps a cool mnemonic tip would help them with correct interpretation
Do you have a cool, undergraduate-level tip about how to correctly interpret p values vs significance level $\alpha$? I haven't come across any such tip.
 A: This surely will not top the list of possible "cool undergraduate-level tips", but simply recalling the definition of a p-value might be helpful (quoted from Wikipedia):

The probability of obtaining test results at least as extreme as the
results actually observed, under the assumption that the null
hypothesis is correct.

So the smaller the probability, the smaller significance level at which we are willing to reject.
A: The standard mnemonic for remembering how to make a conclusion in a hypothesis test is:

If p is low, the null must go!

As to why this is the case, the best explanation of a classical hypothesis test is that it is the inductive anologue of a proof by contradiction.  In a proof by contradiction we begin with a null hypothesis, show that this leads logically to a contradiction, and therefore reject the initial premise that the null is true.  In a classical hypothesis test, we begin with a null hypothesis, show that this leads to a highly implausible result in favour of the alternative (so not quite a deductive contradiction, but close), and therefore reject the initial premise that the null is true.  The p-value in this test is the probability of a result at least as conducive to the alternative hypothesis, assuming the null is true (see formal explanation here).  If this is low then it means that something very implausible happened (under the assumption that the null is true) which gives the "contradiction" in the "inductive proof by contradiction".
