Punjab Forecast: Prannoy Roy’s Nate Silver-Donald Trump Moment???
Tuesday, February 07, 2017
When Dr Prannoy Roy switched from his usual votes, seats, shares and swing projections to dishing out probabilities, he was actually playing chicken à la Nate Silver of the website www.fivethirtyeight.com, an American statistician and writer who analyzes baseball and elections. He is the editor-in-chief of ESPN's FiveThirtyEight and a Special Correspondent for ABC. Silver is not merely a living icon in the US but the world over. But Silver still finally suffered his Waterloo moment with Trump’s victory.
Vote
shares, seat shares, swings are measurable, reflecting a higher degree of certainty
and thus lend themselves to public accountability. Probabilities are vastly different.
Like Silver, Dr Roy too now can take the route to argue that his probability of
AAP winning 57.5% (read here)
theoretically is merely a forecast and not a prediction. The difference between
the two terms is that essentially a forecast is not a certainty but just “an
estimate of risk”. What is overlooked is that Dr Roy’s probability implicitly also
gave AAP 43.5% chances of losing!! In short, whichever way the result went, a
pollster who dishes out probabilities still can claim his forecast was spot on
just as Silver continues to do so with his probabilities of the US Presidential
elections last year. Never mind that millions of Nate followers took his
numbers literally ended up feeling betrayed and deeply let down by their
prophet! Trump’s victory also heralds the death of their prophet!
Then
there is Michael Moore, internationally acclaimed documentary producer. Being a
diehard Left liberal with a deep seated hatred for Donald Trump is a characteristic
trait he shared with Nate Silver. But there the comparison ended. Right from
the primaries when Nate dismissed Trump as a non viable candidate, Moore in
contrast, even in the early days of the US primaries, warned the liberal
movement of the dangers of the rise of Trump and campaigning for Left Liberal
Bernie Sanders who he felt had the best prospects of trouncing Trump. But unlike
Nate who used numbers, Moore relied on more qualitative interpretative
arguments. It is easy to get carried away with numbers and as a result, the
liberal movement preferred to embrace Silver’s forecasts with both hands and
chose to dismissively ignore Moore who in hindsight is now widely accepted had
been perceptibly right on target.
Today
in India we have a choice. Either go for dazzling numbers dished out by the
likes of Prannoy Roy, Yashwant Desmukh etc or go by the field reports of old
time style journalism from the likes of Shivam Vij, Prashant Jha, Rohini Singh
and so many like them who provide us interpretative answers and not so much
solid but meaningless numbers. I have many times jokingly tweeted to Yashwant
Deshmukh that I have not much faith in the numbers that his CVoter dishes out
but have complete admiration for his more substantive analytical election
related articles. This I suppose holds equally true for all truly psephology
freaks, rather than numbers, go by the analytical reports of the likes of Yogendra
Yadav, Sanjay Kumar and CSDS rather than seductive topline numbers of Today’s Chankaya,
AC Nielson and their likes.
Provided
below are extracts from an excellent article by Marlena Trafas in the Weekender
on lessons learnt from the last US Presidential Elections
While
there are many explanations for how Trump got elected, two stands out in
particular for how well they exemplify the failure of numbers to fully explain
the complex world we live in. One explanation comes from resident Numbers Guy,
Nate Silver, the founder and editor-in-chief of FiveThirtyEight, a site that
“uses statistical analysis — hard numbers — to tell compelling stories about
politics, sports, science, economics and culture.” The other explanation comes
from liberal filmmaker and author, Michael Moore.
A
week after the election, Silver appeared on The Daily Show and was interviewed
by the host, Trevor Noah. The interview began a bit awkwardly as Noah says to
Silver, “Let’s talk about polling. You’re not a pollster, you aggregate the
polls. This entire race you were wrong.” To that Silver responds, “No,” and the
entire audience erupts with laughter.
This
audience response makes perfect sense, as it is now clear that all the
predictions and forecasts and probabilities that expressed very little chance
of Trump winning the presidency were wrong. Now, Silver wouldn’t say they were
wrong. In fact, his entire interview with Noah is a defense of the polls he
used, saying there’s “not an easy television explanation,” saying these were
“some of the best polls,” and that his “forecasts” were actually not
“predictions,” but “an estimate of risk.” He describes percentages and “if
this, then this” explanations based on calculations, maintaining that if there
were a 30 percent chance of rain, people may bring out their umbrellas, thereby
suggesting that people should’ve been worried about the 30 percent chance of
Trump being elected.
Despite
Silver’s reasoning, many everyday people took his numbers to mean that Trump in
fact had no chance of winning. Silver argues that people shouldn’t have thought
that based on the numbers he provided. It’s this frustrating, circular,
contradiction that leads to Noah’s exasperated ending joke, “I’m gonna choke
you right now, Nate Silver.” If one watches the interview, it’s clear that all
the smart talk Silver delivers never really feels like a true answer or
explanation.
When
compared with Moore’s “5 Reasons Trump Will Win,” Silver’s numbers become
abstract and meaningless as they translate why Trump will win into zeroes and
ones. Moore, unlike Silver, uses words — qualitative evidence — history and
sociology to explain the human behavior and feelings that would lead to a Trump
presidency.
Moore’s
reasons range from “The Last Stand of The Angry White Man” to “The Depressed
Sanders Vote,” and reading through them on his website makes it it hard to
discount the fact that they make sense — definitely more sense than Silver’s
mathematical explanation. Moore’s explanations are ones people seemingly only came
to fully realize after the election. But Moore made his prediction in the
summer of 2016. And very few people seemed to take him seriously. The days
before the election I heard hopeful, confident talk of a Madam President, not
wariness about the “Angry White Men” who would vote for Trump because they felt
left behind by the current cultural-political moment.
Put
simply, the guy who used numbers and data and stats incorrectly predicted the
election and the guy who used words, history, and qualitative facts correctly
predicted the election., Leading up to Nov. 9, many hopeful liberals put their
faith in Silver’s numbers rather than Moore’s words to explain how humans would
act that Tuesday. The numerical data was trusted and the numerical data let a
lot of people down.
While
there are many lessons to take away from the election of Donald Trump, one is
that numbers can lie. Math and stats and data points don’t always tell it like
it is. Sometimes you need interpretative answers rather than the “correct” answer.
Sometimes the guy spouting words and using simple addition has a keener sense
of the forces that govern our society than the one using statistical analysis.
Read the full
article: Here
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