Modelling distributions explicitly sounds nice, yes.
Modelling distributions explicitly sounds nice, yes.
If you are not doing something crazy, most reasonable people would agree with your judgement. Conversely, if you are making non-obvious inferences where reasonable people disagree, you are in murky water and no sophisticated statistical method will save you. Math is not magic; theorems merely recycle (launder) modeling assumptions into results.
Only people with prior education/training in statistics are capable of doing this. The people who don't need a textbook.
Something like 60% of US adults read at or below the 6th grade level, and 25% of US adults struggle to comprehend graphs or charts entirely. Someone who has no idea what a standard deviation is can't intuit about distributions. I think you're dramatically overestimating the average person.
I disagree vehemently with this claim. I could cite my experience in teaching this topic to liberal arts / humanities college students in the US, but it is really more obvious than that. Anyone can understand a histogram easily and far more intuitively than they can understand the formula for a standard deviation and whether it must divide by N or N-1. Statistics courses and textbooks get stuck on that kind of pedantry, and most students end up missing the forest for the trees.