Category: Current events

Why did the polls get it so wrong?

Another election, another massive screw up by the “best” pollsters in the business. Yes, excuses will be made about how margins of error are only 1/20 and while rare 1/20 events do happen occasionally (it’s roughly like getting two pair in a five card poker hand on your initial deal), they really don’t happen twice in a row. 

So any attempts to ascribe this to “margins of error”  is complete BS. Clearly these polls are not (and didn’t in 2016) use random samples. The magic didn’t happen because the groundwork wasn’t there. No random samples, no magic.

Here’s another way of thinking about this. If they did use random samples in each election, you could also safely assume the polling result errors in each election are independent events. Which means by the “multiplication of probabilities” result I have talked about before, the odds of two screwups in a row would be >= 1/400 and that just isn’t believable.

So something clearly is wrong in their methodology: they aren’t getting random samples. You can come up with conjectures as to why. For example, a common method to get random samples in polls is to do random dialing of phone numbers. If a certain group is always more likely to hang up on you than another group, randomness ain’t happening. You can attempt to weigh your results to take this into effect, and pollsters certainly claimed they would do that after the 2016 debacle, but whatever they added to their secret sauce in 2020 just made the dish taste worse, not better – that is for sure.

My conclusion after this year’s debacle: absent some methodological innovation, political polling isn’t worth paying much attention to going forward and so neither is the effort put into it – by a lot of really smart people.

That (ex)Google Engineeer’s screed

The screed by the (now ex) Google software engineer is all over the news. While I might have more to say about it soon, I want to point out that his generalizations about the differences between the abilities of men and women are simply a rehashed, recycled and much dumbed down version of the research of people like Simon Baron-Cohen.

And, even if research1 like that of Baron-Cohen’s on the so-called “Essential Difference” is the whole story (about which I have my doubts), Mr. Damore’s problem, as I put it in an unpublished review of Baron-Cohen’s book, which I will post in a few days, is that even if these statistical statements are true: “I am firmly in the camp that feels that people who confuse statistical truths about groups with thinking that the same statements apply to individuals, should stop using up oxygen needlessly.” And while it is true that Damore’s pays lip service to this in his missive, he certainly doesn’t take it to heart!

Or, in other words, companies like Google can and will pick and choose from the very best and, at that level, individual differences will surely dwarf any hypothetical group differences. So my question to Damore is other than your biases and immaturity, what makes you think the “typical” women or African American software engineer at Google isn’t a whole lot smarter than you?

Anyway, Damore was fired by Google which has it’s plus and minuses. And, of course it will be hashed out in the courts and he may or may not have a case–the stories I have read seem to differ on his chances.

But my opinion? Google should not have fired him, instead they should have sent him for some training where he either would or would not learn to understand the effect his words would have on the unbelievably talented female and minority engineers that work at Google and why his screed was just wrong, wrong wrong in so many ways.