wnoise comments on Even if you have a nail, not all hammers are the same - Less Wrong

95 Post author: PhilGoetz 29 March 2010 06:09PM

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Comment author: Rain 30 March 2010 02:16:26PM *  17 points [-]

I don't understand. Why is "they used the wrong statistical formula" worth 47 upvotes on the main article? Because people here are interested in supplementation? Because it's a fun math problem?

In the other comments, people are discussing which algorithm would be more appropriate, and debating the nuances of each particular method. Not willing to take the time to understand the math, it comes across as, "This could be right, or wrong, depending on such-and-such, and boy isn't that stupid..."

I run into this problem every time I read anything on health or medicine (it seems limited to these topics). Someone says it's good for you, someone says it's bad for you, both sides attack the other's (complex, expert) methods, and the non-expert is left even more confused than when they first started looking into the matter. And it doesn't help that personal outcomes can be drastically different regardless of the normal result.

To me, this topic is still confusing, with a slight update toward "take more vitamins." Without taking classes in statistics and/or medicine, how can I become less wrong on problems like this? Who can I trust, and why?

Comment author: wnoise 30 March 2010 04:31:46PM *  9 points [-]

I don't understand. Why is "they used the wrong statistical formula" worth 47 upvotes on the main article? Because people here are interested in supplementation? Because it's a fun math problem?

Both. It's instrumental in that vitamin supplementation is a concern many here have. It's also useful as an example of how studies can have flaws, and how these flaws can be found with surprisingly little analysis. Dissections of bad studies helps us avoid similar flaws in our own conclusions. And there are indeed researchers on LessWrong, as well as motivated laymen that can follow the math, and even run their own mathematical regressions. This truly is valuable.