Math is often much more fun and compelling for some people when you both theoretically prove something works and then also convince yourself of the same thing via a numerical experiment. I’m pretty good at math proofs (pure math PhD, wrote some books and papers), but I still love to do numerical experiments. It’s fun, and you also set yourself up to be able to easily ask different questions that may be very hard to answer theoretically.
Some of you might have just suffered from poor math education. I don't believe anyone capable of learning to program competently lacks the cognitive horsepower to do math competently with more or less equivalent ease. Many do however lack the training.
Part of the problem is that the basic statistical model simply neglects to differentiate between observing and doing, which changes the odds. This is very important when trying to reason about causality. When you observe an association like your thermometer shows a high number when it's warm out it's one thing, but when you set your thermometer to a high number you won't get any warmer. Whereas if you warm the room, your thermometer will rise. This symmetry breaking is captured by something called do calculus.