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I’d go as far as to say that the burden of proof is on anybody claiming that exercise is not as fundamental as eating, sleeping or breathing. So this study seem
by SnowHill9902 4y ago
I’d go as far as to say that the burden of proof is on anybody claiming that exercise is not as fundamental as eating, sleeping or breathing. So this study seems obvious or at least reasonable to me.
- tux3 4y agoThe burden of proof is generally on the person standing up and making a claim, no matter how obvious the claim is or which side they're trying to prove. But even when two people make opposite claims and there's no good consensus either way, trying to assign burden of proof by what seems obvious or reasonable isn't a solution. That just takes you back to two people disagreeing about what is obvious or reasonable, it's just going in circles. Something you can do instead is put burden of proof on the person deviating from the null hypothesis, because everyone can agree on that. Crucially, the null hypothesis does *not* mean the obvious thing, or the expected thing. In the case of whether breathing is fundamental and healthy, the null hypothesis is that breathing does absolutely nothing. And of course it's not very hard to reject that one, the null hypothesis is clearly wrong here. If it really is obvious, then you shouldn't have a hard time rejecting it and all is right in the world. But trying to make a claim that's not so easy to prove, and at the same time trying to escape the burden of proof because it 'seems obvious or at least reasonable' harms your ability to notice when you're wrong. It's dangerous and it's bad epistemology.
- Unity99 4y agoCorrect me if I'm wrong but you can state the null hypothesis arbitrarily: "Breathing does nothing" / "Not breathing does nothing." "Aerobic exercise does not increase the probability of developing metastatic cancer" / "A sedentary lifestyle does not increase the probability of developing metastatic cancer." So, in fact your null hypothesis already has a bias of what you consider the baseline, i.e. yes-cancer or no-cancer. So in essence, you are trying to scientize for the sake of argumentation.
- tux3 4y ago>"Breathing does nothing" / "Not breathing does nothing." Right, but that's because those two are actually the same! The null hypothesis in this case does not directly say whether breathing is good or bad, instead it's a statement about the correlation of breathing to anything at all. If the null hypothesis is true, then breathing or not breathing doesn't have any effect. So the null hypothesis is not pro-breathing or anti-breathing, the null hypothesis is that it just doesn't matter either way and doesn't correlate with anything (like the person staying alive) >"Aerobic exercise does not increase the probability of developing metastatic cancer" / "A sedentary lifestyle does not increase the probability of developing metastatic cancer." With both of those, you can also reformulate them to be a statement about correlation. "What is the correlation between the amount of aerobic exercise that you do and the rate of development of metastatic cancer?" So the null hypothesis doesn't depend on whether you think exercise is good or bad. That's the subtlety. It just says that everything is neutral and nothing has any effect until proven otherwise. That doesn't mean the null hypothesis is always what makes sense, or that it's what you should believe in. Obviously breathing keeps you alive, and exercise has a lot of benefits. It's just a way to keep people from disagreeing about what's obvious and who should prove what. The null hypothesis is really dumb, and it only says that anyone who claims they found a real effect, either good or bad, should prove it. If one person is saying red wine causes cancer, and the other person is saying red wine prevents cancer, then they're both rejecting the null hypothesis, which is that you can't claim red wine correlate with anything until proven otherwise. And I promise this isn't just for the sake of the argument. There's a real difference between the mindset of trying to claim "X is good" or "X causes cancer" because it seems so obvious that someone else should just prove the opposite instead, and the much more boring idea that if something is actually kind of obvious, then you should be able to measure whether it does anything AT ALL in either direction (good or bad), and force the person actually making the claim to reject the null hypothesis.
- Unity99 4y agoThank you for the explanation. As I understand it, correlation is not sufficient to prove causation. "Null hypothesis" is one statistical tool, an abstraction over our understanding of the real world. Consider the case where all of those infected with disease D die, while 99% of those infected with D and treated with T survive. Further consider that T is widely administered. Clearly, the correlation between being infected and dying is very low although with a deeper understanding we know that D in fact causes death.