# How can we infer from the combined p-value of Fisher's method whether the null hypotheses are all true?

Using the R package oolong (oolong), I used Fisher's method to combine the p-values of three binomial tests. I have difficulty understanding the combined p-value. I understood it to mean that the combined p-value tells me whether all null hypotheses were true. What exactly needs to be assessed for this? Reading this Understanding Fisher's combined test, I have two guesses:

1. If the combined p-value is below the significance level chosen for the individual binomial tests, the null hypotheses for at least one test can be rejected.
2. Since Fisher's method is based on the chi-square distribution, the critical value must be calculated depending on the degrees of freedom, as in the chi-square test. If the combined p-value is above the critical value, the null hypotheses for each test can be rejected.

I know that this is a very basic question, but unfortunately I don't know much about statistics and would be really grateful if someone could help me. Any links to tutorials or papers would also be greatly appreciated.