What your professor actually said about Bayesianism is irrelevant; GP is responding to what you said about your professor.
Even before the edit, Ilya had a valid point; after the edit, you look like someone whose identity as a Bayesian has gotten in the way of thinking. No matter what you do, cut toward your enemy.
I replaced “orthodox statistics” with “frequentism” in the post in case that will make people happy, but as I understood him Ilya, wasn’t just complaining about that, but also my own implied support for Bayesianism over frequentism. And maybe the standard LessWrong position on that debate is wrong, but to come in and announce that the LW view is wrong without argument, when it’s been argued for at such great length, seems odd to put it midly.
Ilya comes across as not being aware of how much Eliezer and other people here have written about that debate. In fact, it’s not even clear to me if he understands what someone like Eliezer (or for that matter, an academic epistemologist) means when they say “Bayesianism.”
I realize Eliezer holds great sway on this blog, but I think people here ought to question a bit more closely some of his most winning arguments in favor of casting out frequents for Bayesianism. I’ve only read this blog around 4 times, and each time I’ve found a howler apparently accepted. But putting those aside, I find it curious that the results on psychological biases that is given so much weight on this blog are arrived at and affirmed by means of error statistical methodology. error statistics.com
But putting those aside, I find it curious that the results on psychological biases that is given so much weight on this blog are arrived at and affirmed by means of error statistical methodology.
Speaking as one of the LWers who has spent a fair bit of time reading up on both the heuristics & biases literature and also the problems & misuse of NHST (although I certainly couldn’t compare to your general statistical expertise), my position is basically that there’s no available literature which have examined the H&B topic with a superior methodology (so there’s no alternative we could use) and that on the whole H&B has found real effects despite the serious weaknesses in the methodology—for example, of the Reproducibility Project’s 13 targets, the ones which failed to replicate were priming effects and not the tested H&B effects (eg. sunk costs, anchoring, framing). The problems are not so bad as to drain the H&B results of all validity, just some.
So while the H&B research program is no doubt undermined and hampered by the statistical tools and practices of the researchers involved, there seem little reason to think that the most-discussed biases are pure statistical mirages; and so they are entirely relevant to our discussions here.
(From my perspective, the real question about the utility of the H&B literature to our practical discussions here on LW is not whether they exist in the lab settings they are studied in—it’s clear that they are not artifacts of p-value hacking or anything like that—but whether they operate in the real world to a meaningful extent and shape opinions & actions on a wide scale and on the topics we care about. This is, unfortunately, something which is very difficult to study no matter what methodology one might choose to use, and for this concern, criticizing the use of error statistical methodology is largely irrelevant.)
[They were also complaining about] my own implied support for Bayesianism over frequentism.
I don’t see that anywhere. It’s clear the majority of LessWrong (the actual subject of Ilya’s actual sentences) thinks Bayesian statistics (who was talking about epistemology?) is better—with the possible exception of gwern, who uses whatever is most pragmatic (and who I personally think is the actual winner of this debate).
Ilya comes across as not being aware of how much Eliezer and other people here have written about that debate. In fact, it’s not even clear to me if he understands what someone like Eliezer (or for that matter, an academic epistemologist) means when they say “Bayesianism.”
Even a casual examination of their comment record (or, alternatively, a Google search) would have demonstrated that you’re completely wrong in your assessment. I don’t know any other regular on the site that knows more about statistics.
I don’t know any other regular on the site that knows more about statistics.
Allow me to introduce myself. I make my living as a biostatistician; I am philosophically a Jaynesian, in practice a statistical ecumenist. (I don’t know and don’t claim to know causal inference in anything like the depth that Ilya does—that’s his specialty, just like mine is Bayesian modeling.)
What your professor actually said about Bayesianism is irrelevant; GP is responding to what you said about your professor.
Even before the edit, Ilya had a valid point; after the edit, you look like someone whose identity as a Bayesian has gotten in the way of thinking. No matter what you do, cut toward your enemy.
I replaced “orthodox statistics” with “frequentism” in the post in case that will make people happy, but as I understood him Ilya, wasn’t just complaining about that, but also my own implied support for Bayesianism over frequentism. And maybe the standard LessWrong position on that debate is wrong, but to come in and announce that the LW view is wrong without argument, when it’s been argued for at such great length, seems odd to put it midly.
Ilya comes across as not being aware of how much Eliezer and other people here have written about that debate. In fact, it’s not even clear to me if he understands what someone like Eliezer (or for that matter, an academic epistemologist) means when they say “Bayesianism.”
I realize Eliezer holds great sway on this blog, but I think people here ought to question a bit more closely some of his most winning arguments in favor of casting out frequents for Bayesianism. I’ve only read this blog around 4 times, and each time I’ve found a howler apparently accepted. But putting those aside, I find it curious that the results on psychological biases that is given so much weight on this blog are arrived at and affirmed by means of error statistical methodology. error statistics.com
Speaking as one of the LWers who has spent a fair bit of time reading up on both the heuristics & biases literature and also the problems & misuse of NHST (although I certainly couldn’t compare to your general statistical expertise), my position is basically that there’s no available literature which have examined the H&B topic with a superior methodology (so there’s no alternative we could use) and that on the whole H&B has found real effects despite the serious weaknesses in the methodology—for example, of the Reproducibility Project’s 13 targets, the ones which failed to replicate were priming effects and not the tested H&B effects (eg. sunk costs, anchoring, framing). The problems are not so bad as to drain the H&B results of all validity, just some.
So while the H&B research program is no doubt undermined and hampered by the statistical tools and practices of the researchers involved, there seem little reason to think that the most-discussed biases are pure statistical mirages; and so they are entirely relevant to our discussions here.
(From my perspective, the real question about the utility of the H&B literature to our practical discussions here on LW is not whether they exist in the lab settings they are studied in—it’s clear that they are not artifacts of p-value hacking or anything like that—but whether they operate in the real world to a meaningful extent and shape opinions & actions on a wide scale and on the topics we care about. This is, unfortunately, something which is very difficult to study no matter what methodology one might choose to use, and for this concern, criticizing the use of error statistical methodology is largely irrelevant.)
I don’t see that anywhere. It’s clear the majority of LessWrong (the actual subject of Ilya’s actual sentences) thinks Bayesian statistics (who was talking about epistemology?) is better—with the possible exception of gwern, who uses whatever is most pragmatic (and who I personally think is the actual winner of this debate).
Even a casual examination of their comment record (or, alternatively, a Google search) would have demonstrated that you’re completely wrong in your assessment. I don’t know any other regular on the site that knows more about statistics.
Allow me to introduce myself. I make my living as a biostatistician; I am philosophically a Jaynesian, in practice a statistical ecumenist. (I don’t know and don’t claim to know causal inference in anything like the depth that Ilya does—that’s his specialty, just like mine is Bayesian modeling.)
Nice to meet ya! Consider myself updated :)