stdbrouw

50 ms·

511.
by stdbrouw 10y ago
That's kind of the point, though, he's showing the roots of modern management practices go back to that era.
512.
by stdbrouw 10y ago
Some people enjoy reading for its own sake.
513.
by stdbrouw 10y ago
This is an almost arbitrary distinction. These people are looking for a better life, one without violence but hopefully, yes, also one where they're not stuck in poverty. Maslow's pyramid and all that.
514.
by stdbrouw 10y ago
Original study: http://archivesic.ccsd.cnrs.fr/sic_01158395/document
515.
by stdbrouw 10y ago
> I think the way to get the best out of people is not to pander to them to make them the happiest people but to expect high standards from them, to expect everyone to give their best, work well and hard and be proud of what they do. Thi
516.
by stdbrouw 10y ago
That is interesting! Re: researcher degrees of freedom, it's not really about multiple comparisons but about the fact that as an analyst you can make lots and lots of choices about how to construct your model that, individually, might
517.
by stdbrouw 10y ago
> These are technically related, but I think it would be clearer to have two distinct terms for them. "Fishing" and "researcher degrees of freedom" are two terms I hear a lot in reference to fitting models in a very d
518.
by stdbrouw 10y ago
> My approach when developing a predictive model has been always to throw the kitchen sink into a stepwise regression and then eliminate parameters based on their F Values. Is there a better way to do variable selection? It depends on wh
519.
by stdbrouw 10y ago
Yep. It can be hyperparameters ("knobs to tweak" as eanzenberg puts it) but regularization is also often used in a regression context where regularization either pulls parameter estimates for features towards 0 or just kicks out f
520.
by stdbrouw 10y ago
If you know that errors are dependent or if you know the distribution of the error, you can make an even better guess, but that certainly doesn't make averaging "in general not a good idea." You're going to make assumpti
521.
by stdbrouw 10y ago
> The man with two watches knows that one of them is wrong, but only the man with three watches knows what time it really is. I realize it's an off-topic nitpick, but that's not actually true. You take the average of all watche
522.
by stdbrouw 10y ago
Well, in that case calculating the sample mean of a dataset is machine learning too. So is sorting a list alphabetically. Regardless of whether it's supervised or unsupervised, how can you speak of machine learning if the metric is fix
523.
by stdbrouw 10y ago
> humans are visual beings Yep, it's important for a site to be easy to skim, but beyond that, you'd be surprised at how little people care about or note good design. I mean, you're posting this on Hacker News, which can&#
524.
by stdbrouw 10y ago
I must have missed that section where Kuhn explains that fallible evidence is worthless and that everyone should just believe what they want.
525.
by stdbrouw 10y ago
"Knowing" is generally considered to imply that we think something is beyond reasonable doubt. If you can only speak of knowledge in the sense of logical entailment, the word would be useless because then nobody knows anything. W
526.
by stdbrouw 10y ago
Can't say I know what the US curriculum is mostly like, but I was taught about the Bohr atomic model before learning about how they figured out why it wasn't exactly right and we talked about how Newtonian physics was superseded b
527.
by stdbrouw 10y ago
Would you accept a geography text that explains to your kids that the world may be round and that the evidence suggests that the earth is not the center of the universe?
528.
by stdbrouw 10y ago
That's not the point of tokenadult though. He's pointing out that if higher incomes and book reading are both caused by some third factor, encouraging more reading might not have the desired effect on income.
529.
by stdbrouw 10y ago
> nothing exercises every single little muscle in your body - but wrestling does Citation needed.
530.
by stdbrouw 10y ago
It's not necessarily wrong to expect different standards of evidence for different kinds of claims, and to expect a very high standard of evidence for claims that might have profound social implications.
531.
by stdbrouw 10y ago
> The predictor is probably not biased against any particular race - the race_factorAfrican-American:score_factorHigh term is not statistically significant. Or, as ProPublica puts it, it's "almost statistically significant&quot
532.
by stdbrouw 10y ago
Regression works like this: E[Y|X] = Xβ. It is parametric because you model the conditional mean as a weighted sum of various predictors, and these beta "weights" are your parameters. This is true of ordinary regression, Poisson r
533.
by stdbrouw 10y ago
It's not clear to me what kinds of tests you are referring to. Ordinary least squares regression, for example, is all about estimating conditional means, and it is very much parametric. Just finding the best estimates for the paramete
534.
by stdbrouw 10y ago
So, let's say we want to make an industrial process more reliable by reducing the variability of its output. We repeatedly measure the variability by means of MAD. We'd like to know what causes the variability, so we regress MAD o
535.
by stdbrouw 10y ago
And yet a Pareto distribution still has a mean, and the sampling distribution of that mean is approximately normally distributed. Of course I'm not claiming that you can just pretend that a Pareto distribution is a normal distribution,
536.
by stdbrouw 10y ago
That's not a valid reason. You use descriptive statistics when you describe something and you use inferential statistics when you're doing inference.
537.
by stdbrouw 10y ago
MAD is about as simple as it gets, but it is not "the absolute most basic type of summary statistic." In many statistics courses, it is not taught at all, so it's perfectly possible for someone to know how multiple regression
538.
by stdbrouw 10y ago
> A big faux pas I saw a lot was using normality-assumed parametric tests on non-normal data where the skew was clearly significant (i.e. you couldn't get away with it like some non-normal data dists.) Depends on how much data you h
539.
by stdbrouw 10y ago
Only the cream of the crop should get to graduate?
540.
by stdbrouw 10y ago
If you look at the history of statistics, you'll find plenty of practically motivated ad-hoc problem solving like "hmm, how do we get R^n to map onto [0,1]" Log odds were used long before logistic regression and GLMs came alo

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