21–30 of 36 posts
MySQL is perfectly capable of calculating a linear regression for you, btw. In my case, I needed to be able to estimate trends from sparse time series data. Here's how you do that: SELECT @a_count := avg(count) as mean_count, @a_weeks := avg(`week`) as mean_weeks, @covariance := (sum(`week` * `count`) - sum(`week`) * sum(`count`) / count(`week`)) / count(`week`) as covariance, @stddev_count := stddev(`count`) as stdd…
Can someone explain to me why this has (so many) upvotes? This is like elementary undergraduate econ stats and kind of trivial? There's very little content either, it's literally a reformulation of the formula, no interesting graphs or geometric interpretation. What I expected from a title like "Linear Regression By Hand" was the minimization of some quadratic error function, by hand (i.e. using pencil and paper).
https://www.xkcd.com/1053/ I almost certainly know something I'd consider "trivial" that you haven't encountered yet. I try to be really excited when that happens.
Can someone explain to me why this has (so many) upvotes? This is like elementary undergraduate econ stats and kind of trivial? There's very little content either, it's literally a reformulation of the formula, no interesting graphs or geometric interpretation. What I expected from a title like "Linear Regression By Hand" was the minimization of some quadratic error function, by hand (i.e. using pencil and paper).
It's way more fun to know how to derive least squares than to memorize some formula: https://see.stanford.edu/materials/lsoeldsee263/05-ls.pdf (page 4)
Can someone explain to me why this has (so many) upvotes? This is like elementary undergraduate econ stats and kind of trivial? There's very little content either, it's literally a reformulation of the formula, no interesting graphs or geometric interpretation. What I expected from a title like "Linear Regression By Hand" was the minimization of some quadratic error function, by hand (i.e. using pencil and paper).
MySQL is perfectly capable of calculating a linear regression for you, btw. In my case, I needed to be able to estimate trends from sparse time series data. Here's how you do that: SELECT @a_count := avg(count) as mean_count, @a_weeks := avg(`week`) as mean_weeks, @covariance := (sum(`week` * `count`) - sum(`week`) * sum(`count`) / count(`week`)) / count(`week`) as covariance, @stddev_count := stddev(`count`) as stdd…
Yes, but why ? Right tool for the right job and all that...
I share your doubt that this is worth it, to be clear.
MySQL is perfectly capable of calculating a linear regression for you, btw. In my case, I needed to be able to estimate trends from sparse time series data. Here's how you do that: SELECT @a_count := avg(count) as mean_count, @a_weeks := avg(`week`) as mean_weeks, @covariance := (sum(`week` * `count`) - sum(`week`) * sum(`count`) / count(`week`)) / count(`week`) as covariance, @stddev_count := stddev(`count`) as stdd…
Yes, but why ? Right tool for the right job and all that...
The latter might be conceptually cleaner (though it's debatable, relational is a fairly nice programming model and a lot more consistent and well-founded than object orientation, for one), but it's seldom optimal.
Three orders of magnitude or more speedups are not unexpected by pushing the code to the data.
This is very dangerous and an awful way to compute the least squares fit due to potential numerical issues with calculating the inverse of the matrix. I wish he would put a warning in a huge bold header to never do this for actual production work .
Earlier quoted context omitted.
Yes, but why ? Right tool for the right job and all that...
I would guess access to the data is a decent reason to try. No need to pump the data elsewhere, if this is available. I share your doubt that this is worth it, to be clear.
And besides, what happened to the hacker ethos? "Because I can" should be justification enough. :-)