Hacker News Reader

Comment by lostinquebec | Hacker News Reader

The election wins of Trump, Boris Johnson, Brexit and The Liberals in Australia show that data collection really matters. Similarly the financial crisis of 2009 shows that missing data can really matter.

That's the key point of the quote:

> There's something wrong with the way you are measuring it

View on HN

But those are all examples of data collection working fine, though, and people not listening to the data because their anecdotes went the wrong way.

FiveThirtyEight predicted a 28.6% chance of a Trump victory: https://projects.fivethirtyeight.com/2016-election-forecast/ This is a number far greater than zero - it is, for comparison, more likely than flipping two coins and them both coming up heads, or drawing a random card from a deck and having it be diamonds.

Opinion polling of the 2019 Conservative Party leadership election showed Boris Johnson favored to win: https://en.wikipedia.org/wiki/Opinion_polling_for_the_2019_C...

Opinion polling on Brexit showed that it clearly could have gone either way, with a narrow margin between the two options: https://en.wikipedia.org/wiki/Opinion_polling_for_the_United...

I'm less familiar with Australian politics, but assuming you mean the 2013 election, opinion polls showed the Liberals were clearly in the lead: https://en.wikipedia.org/wiki/Opinion_polling_for_the_2013_A...

If people look at data that says "28.6% chance of winning" and they choose to read it as "0% chance of winning," that's not a problem with the way anyone's measuring anything, that's a problem with people trying to treat data as if it's an anecdote.

> I'm less familiar with Australian politics, but assuming you mean the 2013 election

They definitely mean the 2019 election.

I agree it's a bad example re: the Bezos quote, but I also don't think it's an example of anecdotes leading people astray. IMO it's from the brand of bad pop sci that misinterprets perfectly good data while ranting about how amazing science is and how stupid anecdotes are.

> FiveThirtyEight predicted a 28.6% chance of a Trump victory:

This is cherry-picking of the highest widely-known prediction by far, practically an outlier. And I don't think they do any actual polling, just analysis using others' polling data.

I hate to call something gaslighting, but this is gaslighting of the highest order. I am not familiar with Australian politics, but the other three cases were textbook cases of the data saying one thing (Trump might win, BoJo will probably win, and Brexit might happen) and people refusing to believe it.

How these get turned to make precisely the opposite point (Not just by you. It happens all the time) never ceases to amaze me. Presumably the thought process is "I and the people I respect build beliefs based on data. I and the people I respect were wrong. Therefore the data was wrong". Unbelievable.

The Australian election results were within the margin of error of the polls.

https://www.theguardian.com/australia-news/2019/may/19/voter...

What exactly is “the data” that we’re talking about? Is it the measurements that were made, and the methodology used to make them? Or is it the conclusion that something in this case is a “myth”? Because I’d suggest that only one of those things is “the data”, and the other one is a subjective interpretation of it. I’d also suggest that people who have an agenda to promote will often attempt to blur the line as much as possible between empirical measurements, and their own opinions about what they’re supposed to mean.

In this case, the data I am talking about are the polls. Of course, there's a lot of methodology that goes into designing the polls and the data collection process, but those were basically solid and importantly, not subjective.

> I’d also suggest that people who have an agenda to promote will often attempt to blur the line as much as possible between empirical measurements, and their own opinions about what they’re supposed to mean.

This ran rampant in all those cases (Trump, BoJo, Brexit), I agree.

There was data and then there was the NYT saying Hillary has a 99% chance. Ha

Reply on news.ycombinator.com