Not relative to a public universal health care system, no.
I’m saying not at all. With public universal health care, without public universal health care… it does not matter. There is a negative correlation between smoking and life expectancy.
If your diagnosis is “we need to cut cigarette use to save lives”,
Yes, that is a conclusion one could draw from this.
but we’re ignoring the…
For the purposes of discussing this correlation, it does not matter. If we have universal health care, then cutting cigarette use will save lives. If we do not have universal health care, then cutting cigarette use will save lives. Conclusion: cutting cigarette use will save lives. That is true. No amount of discussion about unrelated third variables will make that not true.
If a third variable makes the model better, go ahead and add a third variable. But if someone doesn’t even understand the two-variable model, we should make sure they understand THAT model before we add even more stuff that they don’t understand.
With public universal health care, without public universal health care… it does not matter.
It matters enormously. Literally the difference between surviving and not surviving.
You know, the thing you’re measuring for.
But if someone doesn’t even understand the two-variable model, we should make sure they understand THAT model before we add even more stuff that they don’t understand.
Not for the purpose of establishing whether there is a negative correlation between smoking and life expectancy.
Also that comic is saying that adding a third variable does not always make the model better. Also p-hacking is a thing. It’s the opposite of what you’re trying to establish, which is the existence of a third variable which improves the model. And once again, I will say that if you find two correlated variables confusing, adding a third variable is NOT going to help you.
I’m saying not at all. With public universal health care, without public universal health care… it does not matter. There is a negative correlation between smoking and life expectancy.
Yes, that is a conclusion one could draw from this.
For the purposes of discussing this correlation, it does not matter. If we have universal health care, then cutting cigarette use will save lives. If we do not have universal health care, then cutting cigarette use will save lives. Conclusion: cutting cigarette use will save lives. That is true. No amount of discussion about unrelated third variables will make that not true.
If a third variable makes the model better, go ahead and add a third variable. But if someone doesn’t even understand the two-variable model, we should make sure they understand THAT model before we add even more stuff that they don’t understand.
It matters enormously. Literally the difference between surviving and not surviving.
You know, the thing you’re measuring for.
Not for the purpose of establishing whether there is a negative correlation between smoking and life expectancy.
Also that comic is saying that adding a third variable does not always make the model better. Also p-hacking is a thing. It’s the opposite of what you’re trying to establish, which is the existence of a third variable which improves the model. And once again, I will say that if you find two correlated variables confusing, adding a third variable is NOT going to help you.