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by closed 9y ago
Even though these mindmaps are very simple, and basically re-arranging a table of contents, there's something deeply satisfying about having a bit of spatial layout.
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by closed 9y ago
also, maybe the people they interact with tend to use R, so writing it in that language might give more immediate traction / feedback.
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by closed 9y ago
"Congratulations you have reached complete habituation + crippling dependence!"
304.
by closed 9y ago
Before I started drinking coffee, I had a solid nap flow going. Now that coffee is in the picture, I'd probably just lay there for 20 minutes twitching :/.
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by closed 9y ago
You can beware of something and still read it. In general, I think it's pretty sound advice. It's less about turning your nose up at someone because they're not a professor at Harvard, and more about asking whether a group wi
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by closed 9y ago
I love how simple and clear this post is. As a kind of weird aside, if anyone ever emailed me about any of my journal articles, I would 100% respond to them (assuming they weren't a machine). I think most of my colleagues would do the
307.
by closed 9y ago
This is great advice. Even after becoming familiar with an area, I read some authors and get swamped by unexplained terminology. Another simple trick is to look at the journal title. Articles in journals like "Trends in... " tend
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by closed 9y ago
Other people have covered in detail different approaches to learning, so I figured I'd mention a weird thing that's been helpful for me, in case it's useful. While learning, I try to split off a little piece of myself into a
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by closed 9y ago
Preprints are fine to post, and that's definitely what some people are pushing for. There's a good article on how some psychologists have responded here: http://www.the-scientist.com/?articles.view/articleNo&#
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by closed 9y ago
I ran into Elsevier at a job fair, and had to tell them that my academic advisor would probably see it as me working on the death star..
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by closed 9y ago
A lot of academics I know point people to sci-hub! For example, the American Psychological Association has been issuing take-down requests to academics who distribute final article PDFs on their sites. As a result, there's been a fair
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by closed 9y ago
That's part of what made me curious about LBP+chiropractic research! Pretty wild.
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by closed 9y ago
This made me curious about its effectiveness for back pain, so I tried to find a meta-analysis. Turned up this on plos one. (note, I can't speak for the article's quality). > Moderate evidence suggests that chiropractic care fo
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by closed 9y ago
Really useful to hear, thanks! I know psychology was gaining a lot of headway with NN models in the 90s, but had little sense for what was going on in industry.
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by closed 9y ago
Was this true, or perceived as true in 2003? My understanding was that people did not see them as performing worse than NN back then.
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by closed 9y ago
IRT modeling doesn't care much whether an item is free response or not, just the scale on which it's scored. Binary and polytomous scoring = IRT model. Continuous scoring = Factor analysis. If by mentioning free response, you mean
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by closed 9y ago
I agree with your point, that the average likely misses important factors (and think the tagging you guys are implementing looks really cool!). However, I'd say that the issue is more than having a non-rigorous analysis. It's the
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by closed 9y ago
To be honest, I like that this article tries to perform simple analyses, but find their rationale pretty confusing. This kind of data is commonly modeled using item response theory (IRT). I suspect that even in data generated by a unidimens
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by closed 9y ago
Can you give an example? I have never seen people say it was a failed experiment when it "disproved" a hypothesis. If it was able to disprove something, often that means people perceive a high degree of certainty in the results. T
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by closed 9y ago
Yeah, that's fair. The goals of machine learning and neuroscience seem fairly different. Nobody in ML will complain if your neural network has great prediction but isn't supported biologically. OTOH, neuroscientists might take a m
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by closed 9y ago
> Machine learning at the moment is an empirical science that has made great strides without consulting neuroscience for it. What is your basis for this statement? Consider Geoff Hinton's publishing record, which contains many colla
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by closed 9y ago
My sense is that ecology tends to have more on spatial covariance (along with epidemiology), psychology on building scales out of latent factor models, and economics on temporal covariance. (although there is substantial overlap between the
323.
by closed 9y ago
This library started as a refactor of that project, after it laid broken and unmaintained for a long time. Having followed the yhat ggplot for a long time, I've lost faith that it will be actively maintained.
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by closed 9y ago
I watched your refactor of yhat's py ggplot branch, and was disappointed when glamp dropped in a totally new implementation out of the blue. Thanks for all your hard work--glad it is it's own package now :).
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by closed 9y ago
Sometimes you are very certain prior to updating your beliefs (in the form of a posterior), which can lead to very sharp predictions from (and possibly in spite of) your data.
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by closed 9y ago
The point is that you can view things as a (approximate) form of bayesian inference, in order to think differently about how they work, and what they're doing. Another common example is ridge regression being expressed as a bayesian re
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by closed 9y ago
> We measure a model’s quality in two ways. First, we evaluate the model using a well-defined accuracy metric we compute during model training. This measure tells us how well the model performs its task – specifically, giving engaging Tw
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by closed 9y ago
Wansink strikes me as an extremely bright, creative researcher. His problem seems to be that he didn't collaborate with people who were strong methodologists. If anything, he reminds me of a lot of brilliant researchers, who are too co
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by closed 9y ago
Interestingly, a few years ago Nature planned to include statisticians... > as consultants on the rare papers in which there are serious issues about the statistical techniques used, at the editor's discretion and based on the refer
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by closed 9y ago
It sounds like OP's feedback is not that you shouldn't take risks, but that they think the risks you took may backfire with investors. (Or rather would backfire with OP, an investor, or someone taking that perspective).

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