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Stony Brook University Professor Helmut Norpoth has created a statistical algorithm that uses a candidate’s performance in party primaries and patterns in the electoral cycle to forecast the winner of the presidential election.
Should Trump follow through on his huge momentum and become the Republican nominee, he has a 97% chance of beating Hillary Clinton and a 99% chance of beating Bernie Sanders in the general election, according to Norpoth, who presented his findings at the SUNY Global Center in Manhattan earlier this week.
“The bottom line is that the primary model, using also the cyclical movement, makes it almost certain that Donald Trump will be the next president,” Norpoth told The Statesman, “if he’s a nominee of the [Republican] party.”
Political Science Professor: Trump Has 97-99% Chance of Becoming President
“The probability of that [outcome] is almost complete certainty, 97 percent. It’s almost ‘Take it to the bank,’” said the professor.
originally posted by: Abysha
a reply to: Profusion
Wouldn't you rather trust a university with a 100% prediction record. Western Illinois University has never been wrong and they called Sanders months ago.
originally posted by: DexterRiley
I followed the link to the article, and a link within the article, but I can't find any paper that describes how the professor's statistical model actually works. The commenters to those articles also question where his evidence is.
I have my doubts about its validity.
-dex
originally posted by: Profusion
Professor: Trump Has 97-99% Chance of Becoming President (if he’s the RNC nominee)
Thanks to your link to Stony Brook University I was able to find a link to his 2012 Statistical Model as well other related material.
I'm sure he's swamped with emails at the moment but if you do email him and he sends you his model, please post it here.
It actually does meet some of the necessary parameters for a predictive programming effort:
Incidentally, when I saw all the news reports of his forecast on Google, the first thing that came to mind was "predictive programming"...
originally posted by: DexterRiley
a reply to: Profusion
Thanks to your link to Stony Brook University I was able to find a link to his 2012 Statistical Model as well other related material.
I'm sure he's swamped with emails at the moment but if you do email him and he sends you his model, please post it here.
A cursory view of the write-up leads me to believe that Dr. Norpoth is no quack. He also has references to at least 7 different publications that have directly covered this prediction. This certainly lends an air of authenticity to his work.
It actually does meet some of the necessary parameters for a predictive programming effort:
Incidentally, when I saw all the news reports of his forecast on Google, the first thing that came to mind was "predictive programming"...
1. It is an outrageous prediction that subconsciously suggests to people that this is a foregone conclusion.
2. By demonstrating such a broad difference in support for each candidate, it would suggest to those who want to be on the winning team to establish loyalty to the predicted winner. There are people who will vote for whom they believe will be the winner, rather than his or her policies.
3. It introduces a more concrete possibility of losing into the mind of the predicted loser's supporters. Though it may also make them work harder to get their candidate elected.
4. Not to mention that polls can take on lives of their own and influence one another. Might as well get into the game early.
-dex
This forecast was made using the electoral cycle model, which studies a pattern of voting in the presidential election that makes it less likely for an incumbent party to hold the presidency after two terms in office. The model does not assume who would be the party nominees or the conditions of the country at the time.
In 1982, the Hunt Commission recommended and the Democratic National Committee adopted a rule that set aside some delegate slots for Democratic members of Congress and for state party chairs and vice chairs. Under the original Hunt plan, superdelegates were 30% of all delegates, but when it was finally implemented for the 1984 election, they were 14%. The number has steadily increased, and today they are approximately 20%.