You take your ‘significance’ level and divide by the number of tests you are doing.
So if you have set ‘significance’ at 0.05, and do 5 different statistical tests, to be actually sure that your “rejection of the null hypothesis” (aka – it’s significant! it works!), you need to see the result to be
0.05 / 5 = 0.01 …. so …
p <0.01 before you can really call it a ‘significant’ result.
(It’s a bit harsh. It probably makes you make too many type II errors.)
(You can also apply it to correct confidence intervals. Do five tests, for the ‘real’ 95% confidence interval for each one, you need to calculate the 99% confidence interval.)