Can you unpack their explanation of [5]? It rings false to me, because I think it's based on a false assumption of the distribution of baseball weights. I thi

Can you unpack their explanation of [5]? It rings false to me, because I think it's based on a false assumption of the distribution of baseball weights. I think their assumptions are that both the weights of the total ball and weight of the core follow normal distributions, but after showing that the cores do not, they continue to assume that the weight of the whole balls does. This feels like one of the classic critiques of frequentist statistics, where effect size gets conflated with sample size. Worse, shouldn't we presume that there is a (strong) quality control step, which eliminates the tails of the distribution for overly heavy and overly light balls, but perhaps not for heavy and light cores? Which means that our assumptions that both the cores and balls follow the same normal distribution for ball weight is wrong from the start, and thus the notion of "statistically significant" shouldn't depend on total weight of the ball. That is to say, I think the evidence is just as strong that the cores are .5 g lighter as that the balls are .5 g lighter, but it's just a quirk of p-value and our (known-to-be-false0 assumptions of normal distribution that make one conclusion "significant" and the other "not significant". They did find that the balls were .5 g lighter, right?