I always appreciate it when other data scientists talk about making their data tell a story that upper management already decided they wanted confirmed for them. Makes me feel less alone. Thank you
In light of all that, making decisions by gut feelings or intuition is, if nothing else, at least honest, and probably just as good an approach as anything else.
If we were all to iteratively acknowledge our interests to a greater degree then we could probably learn a lot more from data but I think there is a strong message in our society that self interest is wrong and so people dedicate great energy to pretending that their self interest does not exist.
I went down on this thought once, and I became antiscience. Reasoning-wise I only trust what I can understand, simple highschool level reasoning. Anything that I can't understand, and is more sophisticated than a highschool level reasoning I don't trust. I mean, sure, there are facts that need complicated statistical methods. But I can't check them, I don't trust authority, (and probably they are more often wrong than right anyway, because they need results or they starve to death), so I reject them/I am ambivalent.
Like what? There are ideas that need causal reasoning, or trust that it exists behind things you don't fully understand. Statistics, especially anything higher order, end up being basically just rhetoric, outside maybe of some very narrow claims.
If someone tells you you need a bunch or statistics to understand something, they're almost certainly trying to persuade you without having a strong enough logical footing to just explain themselves.
And science isn't a religion or a position, you can't really be for or against it. That should be a starting point.
Causal mediation analysis is similar if you want to understand what assumptions you really need to make to talk about the mechanisms through which a treatment effect acts on the outcome.
If you're talking about optimizing around some agreed upon thing, sure I can understand the idea of using some more complex statistical analysis (though I might question the incremental value).
To understand when a simple answer is unlikely to be correct, you do benefit from understanding the mathematics. There’s a reason that people with doctorates in statistics spend 8 to 10 years in school to learn how to contribute to it.
https://github.com/patricktrainer/csuite-saas-metric-generat...
It’s public perception of modern science that is that way (in large part because of politicians).
Still bad, but a different kind of bad.