Say we have some data with many parameters. As an example let's say I'm an not-so-ethical journalist working for a food website and I'm looking to write some clickbait article "backed by science" about how some food or lifestyle is good/bad for you.
My data might contain a set of thousands of people, their socioeconomic status, what they had for breakfast, whether they're vegetarian, whether they prefer tea or coffee, etc. and also what their scores are for an IQ test.
If I split the dataset into many (100+) groups, where group one might split vegetarians/meat eaters, group two might split coffee drinkers and tea drinkers, group 3 might split female coffee drinkers and male tea drinkers etc. If then use ANOVA to compare all groups to see if there's a statistically significant difference, is this not effectively p-hacking?
I understand that ANOVA won't tell us which groups are different, but it seems like it would be a quick way to confirm that there IS a (false) positive in there. And then it's a case of finding out which groups are different.