I am interested in cases where almost
everyone seems to believe something that is actually NOT true.
An interesting example from the 2016
election is that most people seem to believe that: THE POLLS WERE
WRONG! I have heard Trump supporters say this and I have heard Trump
opponents say this. It is accepted by so many people on both sides of
the political divide that it might seem crazy to even challenge it
now.
But maybe these are the beliefs - the
ones most widely and unquestioningly accepted - that we most need to
challenge.
So is this belief true? Were the polls
really wrong in 2016?
Let's consider what the polls were
saying just before the election. Here is an article that came out the
day before the election that discusses the latest poll results. It is
called “Presidential Election Polls for November 7, 2016” and
appeared in Newsweek.
According to this article “Democratic
presidential nominee Hillary Clinton leads her Republican rival
Donald Trump by 2.5 points, according to the Real Clear Politics
average of most state and national polls. Clinton has 46.8 percent
of voter support compared to Trump's 44.3 percent.”
The article also says that “Forecasts
still show Clinton winning the election. “FiveThirtyEight” shows
Clinton with a 65.5 percent chance of winning the election, while
Trump has a 34.5 percent chance of victory.”
***
[So why did Hillary lose in 2016? Read this new book to find out.]
[If you want to support
"Anything Smart" just click on book links like the one
below to buy your books. "Anything Smart" will receive a
commission. Thanks!]
***
There is additional information in this
article but I will focus on the two extracts above to evaluate the
claim that “the polls were wrong.”
Before we look at the results of the
election I would like to consider four points about the information
above: what polls do, what “chance” means, the danger of lazy
language, and what did these polls actually measure?
1. What do polls really do?
First, what do polls really do? Well,
for one thing, polls do NOT predict the future. Polls tell you what
answers people gave at a certain point in time. When you take polls
at different points in time you get different results. If people who
say “the polls were wrong in 2016” mean that the polls predicted
Hillary would win but then Hillary lost, then that just means these
people don't understand what polls do.
According to the article we quote from
above Hillary had 46.8 percent of voter support at the time the polls
reported on were taken. That does not PREDICT she will get 46.8
percent of the vote at some later date. If the election were still
several weeks away many things might change, and many voters might
change their minds, between the poll and the election. On the other
hand, it is probably logical to assume that, if nothing significant
has changed between the polls and the election, then Hillary will
probably get about as much support as she had in the poll. But this
is an ASSUMPTION based partly on the poll and partly on the belief
that nothing has changed since the poll. The poll ITSELF does not
predict anything about the future.
2. What does "chance" mean?
Second, what does “chance” mean?
The article we are studying here says that Hillary has a 65.5 percent
chance of winning the election. This does not mean that Hillary will
win! It means exactly what it says, Hillary has a 65.5 percent chance
of winning.
Let's illustrate this with an example.
Suppose I give you two coins and a cup. I tell you to shake up the
coins in the cup and then toss them out onto a table. I tell you
“there is a 75 percent chance that there will be at least one head
showing when you toss these coins onto the table.” You toss the
coins and we see there is no head showing. If you then say, “Ha ha.
Your prediction was wrong” you would be mistaken. I did not predict
there would be a head showing, I just said there was a 75 percent
chance that there would be a head showing and that statement is
absolutely true even if, on any particular toss, no head is showing.
This is the same thing that happened to
forecasters in the 2016 election. The polls themselves did not
predict anything. The forecasts, based partly on polls and partly on
other information, did not predict anything either. They did try to
calculate the “chance” or “probability” that Hillary would
win, and the fact that Hillary lost does not prove those calculations
were wrong any more than getting no head when tossing two coins
proves that there is NOT a 75 percent chance of seeing at least one
head.
[Note: One big difference between
tossing coins and having elections is that we can toss the coins many
times to see if the calculated 75 percent chance of seeing at least
one head really works out over many tries, while we cannot repeat an
election many times to see if the calculated probability was correct.
Still, the principle is the same. If the probability of something
happening, like Hillary winning, is calculated as 65.5 percent, the
mere fact that she did not win does not prove that the calculated
probability was incorrect.]
3. The danger of lazy language
Third, the danger of lazy language. One
of the statements from the article we quoted above is “Forecasts
still show Clinton winning the election.” This certainly looks like
a prediction that Hillary will win. Notice first, that this statement
is not saying that polls show Clinton winning, but rather that
forecasts show Clinton winning. But is even that LITERALLY true?
The statement above is immediately
followed by another statement that explains what the author means.
“FiveThirtyEight shows Clinton with a 65.5 percent chance of
winning the election, while Trump has a 34.5 percent chance of
victory.” In other words, saying that forecasts show Clinton
winning just means that forecasters have calculated that Clinton has
a higher probability of winning. As we showed above, even if Hillary
loses, which she did, that does not prove that the calculation of her
probability of winning was incorrect.
The problem here is just that people
sometimes save time by using lazy language. Instead of saying the
more accurate “Forecasts calculate that Hillary has a 65.5 percent
chance of winning the election” sometimes people take a shortcut
and say the less accurate “Forecasts show Hillary winning the
election.” We have to be on the lookout for this kind of lazy
language and it should usually be fairly obvious from the context of
what we are reading.
4. What did the 2016 polls actually measure?
Fourth, what does the poll actually
measure? The poll results quoted above, from just before the
election, are talking about popular vote and not Electoral vote. It
is natural to assume that whoever wins the popular vote will also win
the Electoral vote because that is what usually happens. But it does
not ALWAYS happen and 2016 was one of those unusual years when the
winner of the popular vote did not also win the Electoral vote.
So here again, the fact that Hillary
lost the Electoral vote on election day does not mean that a poll
measuring popular vote a few days before the election, was wrong.
With all of these technical
preliminaries out of the way we are finally ready to look at what
actually happened in the election. According to the American
Presidency Project Hillary ended up with 48.2 percent of the vote and
Trump got 46.1 percent of the vote.
What did the last polls say just before the election? According to
the article we are discussing the average of poll results was 46.8
percent for Hillary and 44.3 percent for Trump.
This is pretty close agreement between
the polls and the election, isn't it?
- The polls showed Hillary at 46.8 percent and she actually got 48.2 percent. A difference of just 3%.
- The polls showed Trump at 44.3 percent and he actually got 46.1%. A difference of just 4%.
- The polls showed Hillary ahead by 2.5 percentage points and at the time of the election she led by 2.1 percentage points.
Anyone who says the polls in 2016 “got
it wrong” should take a close look at these numbers. The polls got
it right! What caused the surprise was an incorrect assumption that
whoever wins the popular vote will also win the Electoral vote.
***
[So why did Hillary lose in 2016? Read this new book to find out what her explanation is.]
[If you want to support
"Anything Smart" just click on book links like the one
below to buy your books. "Anything Smart" will receive a
commission. Thanks!]
***
Copyright © 2018 by Joseph Wayne Gadway