dbroockman

When Uber re-launched quasi-legally in Austin, TX, some drivers there told me Uber promised to pay any fines they incurred. Whether the German government fines Uber and/or the drivers, maybe they're just hoping to throw money at the problem.

Or maybe just "the kind of employees who get paid less also are the kind of people who have a harder time getting new jobs." Correlation != causation.

In Hawaii all beaches are public property and maintaining public access routes (and parking!) to all beaches is required by law. If rich Californians keep up this crap, they might just inspire a voter initiative that would make things even worse for them.

I assume most of the people who go to that review page are the ones with bad experiences? Otherwise, who would review a power adapter?

Listen in on the phone conversations a plumber has and you'd get the impressions that no one's pipes work.

The author subsequently scored a gig at the WSJ with multiple columns.[1] Funny how the ability to accurately comment on industry is not a useful qualification for being employed to comment on industry. :) (Written somewhat tongue-in-cheek obviously, I'm sure he has gotten lucky before with predictions before too.)

[1] https://twitter.com/mattlynnwriter

Should we change our beliefs based on this post? Based on Dorian's denials today, isn't this post just as likely in the world in which Dorian is Satoshi and the world in which Dorian is not? I don't have a strong belief one way or the other, but this doesn't seem like good evidence.

The "regression to the mean" and "novelty" effect is getting at two different things (both true, both important).

1. Underpowered tests are likely to exaggerate differences, since E(abs(truth - result)) increases as the sample size shrinks.

2. The much bigger problem I've seen a lot: when users see a new layout they aren't accustomed to they often respond better, but when they get used to it, they can begin responding worse than with the old design. Two ways to deal with this are long term testing (let people get used to it) and testing on new users. Or, embrace the novelty effect and just keep changing shit up to keep users guessing - this seems to be FB's solution.

There's a big (and common) error in statistical reasoning Google is making with the decision to down-weight GPA based on their data: That GPAs do not predict performance among those it hired does not imply that Google should not use GPA when hiring any more. Rather, it means that Google used GPA to exactly the right extent among those it hired under its old policy - there was no information left in GPA they didn't use, and therefore they should leave whatever policy they have in place as is.

Explanation: suppose there are only two things Google observes, GPA and coding ability, and that Google uses some correct decision rule to only hire those people where the sum GPA + coding ability > some threshold. Those who have lower GPAs will thus tend to have higher coding ability, otherwise they wouldn't have met the threshold to make it into the pool of hires they're analyzing - and, therefore, comparing "those with low GPAs that Google hired" and "those with high GPAs that Google hired" is not an apples-to-apples comparison.

In order to assess whether GPA should be used at all, they would need to look at how the people they didn't hire because of their existing policy would have performed.

More reading: http://beerbrarian.blogspot.com/2013/11/the-subtle-joys-of-s... and http://www.jamesmahoney.org/articles/Insights%20and%20Pitfal...

We know from randomized trials on legislators that calls do work in changing their positions. http://themonkeycage.org/wp-content/uploads/2013/04/berganco...

89k is actually a very large number.

On #1: If the TSA didn't frisk 80 year old men, any smart terrorist would begin recruiting 80 year olds. You can't have gaps in enforcement by policy or they will be exploited (sadly).