News Who Will Win the Elections? Predictions and Analysis

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The discussion centers around predictions for the upcoming elections, with participants expressing uncertainty about the outcomes between Obama and Romney. Many believe the race is extremely close, with some polls showing Romney slightly ahead, while others indicate Obama has the advantage due to endorsements and debate performance. The impact of Hurricane Sandy on voter sentiment is debated, with some arguing it has complicated Obama's chances, while others note his effective response to the crisis. The electoral map suggests that Obama has a clearer path to victory, needing fewer swing states compared to Romney, who must secure multiple key states to win. Overall, the consensus leans towards an Obama victory, despite the tight race.

Who will win elections?

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  • #101
russ_watters said:
Clearly, if you have two identical polls with a certain margins for error, you should be able to combined them to make one big poll with a lower margin for error. But that requires that the polls actually be identical and I'm not sure they actually are. I'm having some trouble finding how RealClearPolitics does its aggregation, but Nate Silver provides a little insight: http://fivethirtyeight.blogs.nytime...but-obama-remains-electoral-college-favorite/

This at least gives us the lower limit on the error. The best it could possibly be is 2% if all the polls were conducted identically, which of course, they were not.

Err... I don't know every branch of statistics, but every time I've used statistics combining data sets, the the combined data set does not have a lower error margin than both of the constituents. It is found in a pythagorean fashion, so it always ends up being more than the max of error margins of your constituent datas.

like 2 and 3 MOE's would give an aggregated MOE: sqrt(2^2 + 3^2) = 3.6
 
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  • #102
Pythagorean said:
Err... I don't know every branch of statistics, but every time I've used statistics combining data sets, the the combined data set does not have a lower error margin than both of the constituents. It is found in a pythagorean fashion, so it always ends up being more than the max error margins of your constituent datas.

I think you are confusing variance (which does behave as above) and error margin (i.e. variance expressed as a percentage of population size.

For n Bernouilli trials, the variance = ##np(1-p)## which clearly increases as n increases. But the expected error is proportional to ##\sqrt{n}## (i.e. the standard deviation), and expressed as a percentage of the sample size it is proportional to ##1/\sqrt{n}##.
 
  • #103
It was explicitly error aggregation.

Here is a powerpoint from the state data center of www.census.gov that uses the same convention:

"www.census.gov/sdc/trent.ppt"
 
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  • #104
Though I do agree that they use the variance in the above examples (as I was taught to). Margin of error is defined elsewhere with the 1/sqrt(n). I think within one study, you surely use the 1/sqrt(n).

But aggregation, I'm not so sure about. I remember learning that errors from different sets should compound, not cancel. But this is from classes, not real research experience.
 
  • #106
I think the race is a coin toss right now. However, things have moved much better for Obama over the last week or two. Obama has been an extremely lucky politician I think, in that the media has covered for him regarding this whole Benghazi issue, and then Hurricane Sandy cut into the momentum Mitt Romney had.
 
  • #107
Pythagorean said:
Though I do agree that they use the variance in the above examples (as I was taught to). Margin of error is defined elsewhere with the 1/sqrt(n). I think within one study, you surely use the 1/sqrt(n).

But aggregation, I'm not so sure about. I remember learning that errors from different sets should compound, not cancel. But this is from classes, not real research experience.

I'll pass on the terminology (even if I could remember what it was when I last took a stats course, it's probably changed since then!) and stick to a common sense example.

Suppose you have a fair coin and toss it twice. The maximum "sampling errot" in the number of heads is ##\pm 1##, but you have a 50% chance of getting a 50% sampling error - i.e. getting 0% or 100% heads when the "true value" is 50%.

On the other hand if you toss it 1,000,000 times, the number of heads you get will probably be several hundred away from the expected value of 500,000, but a percentage sampling error from getting 501,000 heads instead of 500,000 is only 0.1%.
 
  • #108
Certainly. My hesitation was, from my data aggregation exposure, the two sample were collected with different methodologies and the errors weren't just a sample size issue. There were Other measurement errors associated with the data sets.

An additional curiosity: do all polls assume a uniform distribution?
 
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  • #109
Pythagorean said:
An additional curiosity: do all polls assume a uniform distribution?
Of what? I suspect the answer is no...
 
  • #110
It always of whatever you're measuring. So for penny, we assume a uniform distribution of heads and tails. Here it would Romnians and Obamians. I don't know what else you could do besides assume uniform, or rather, how you would motivate it.
 
  • #111
Pythagorean said:
It always of whatever you're measuring. So for penny, we assume a uniform distribution of heads and tails. Here it would Romnians and Obamians. I don't know what else you could do besides assume uniform, or rather, how you would motivate it.
Still not following. A "uniform distribution" doesn't compute to me - it implies a 50/50 split between Romney supporters and Obama supporters, which would always give a 50/50 poll result, wouldn't it? But let me explain in more detail:

The polls do correct for the demographics of the sample, including the fraction of Democrats and Republicans sampled, Women and men. Whites and minorities. Etc...though not all polls will correct for all demographics or by the same amount. Ie, you don't correct the sample to make it 50/50 democrats vs republicans unless you think that an equal number of registered democrats and republicans will vote. That's where a lot of voodoo creeps into the polls. How do you figure out before the election what the split will be between registered democrats and republicans?

In addition, response rates for polls are very low, which can make for an additional source of error not quantified (and not quantifiable). In other words, a poll that says it has an error of 3% is really saying that of the 9% of people who respond to polls, it has an error margin of 3%. But what about the other 91% of people who wouldn't even answer the poll? How would they vote? We don't know, but using the poll assumes that they would answer the same way. That's a pretty big assumption.
http://web.mit.edu/newsoffice/2012/explained-margin-of-error-polls-1031.html
 
  • #112
BBC seems to be giving both candidates 50-50 chances of winning in their opinion and other articles. They have been critical of Romney as well of Obama.
 
  • #113
In addition, response rates for polls are very low, which can make for an additional source of error not quantified (and not quantifiable).

Yes, absolutely- but this is true of the individual polls as much as the aggregates. We still expect aggregates of polls to reduce the quantifiable sampling errors. If all the state polls are biased (because people not responding are planning to vote radically differently), then its garbage in -> garbage out, of course.
 
  • #114
It always of whatever you're measuring. So for penny, we assume a uniform distribution of heads and tails. Here it would Romnians and Obamians. I don't know what else you could do besides assume uniform, or rather, how you would motivate it.

I think you are confused. The goal of polling is to figure out what the underlying distribution looks like- if pollsters just assumed the underlying distribution were uniform, then what's the point of the poll?

Imagine someone gives you a penny and says 'this might be biased, I don't know'. Whats your methodology? You flip the coin a bunch and see what it comes out. You know you only have two outcomes, so the underlying-distribution of the coin is some sort of binomial http://en.wikipedia.org/wiki/Binomial_distribution distribution.

Now, you flip the coins N times, and you ask "what binomial distributions are consistent with the results I have?" And that sets your estimate for the probability of getting heads with your (potentially) biased coin.

As to your question about combining samples reducing error- if you flip the coin 100 times do you think you'll have a better or worse estimate than if you fip the coin 1000 times? 10000 times?

As to non-sampling errors, its hard to make a model with any kind of random-error that won't average out by aggregating the polls. However, systematic errors that are present across polls (imagine that 3/4 of the population of a state only spoke Lortax, an alien language, and that everyone who spoke Lortax were planning to vote not for Romney, or Obama, but for Kang. By not conducting polls in Lortax, every poll is systematically biased against Kang) won't cancel out, but they won't grow by including more polls.
 
  • #115
ParticleGrl said:
I think you are confused. The goal of polling is to figure out what the underlying distribution looks like- if pollsters just assumed the underlying distribution were uniform, then what's the point of the poll?

Imagine someone gives you a penny and says 'this might be biased, I don't know'. Whats your methodology? You flip the coin a bunch and see what it comes out. You know you only have two outcomes, so the underlying-distribution of the coin is some sort of binomial http://en.wikipedia.org/wiki/Binomial_distribution distribution.

Now, you flip the coins N times, and you ask "what binomial distributions are consistent with the results I have?" And that sets your estimate for the probability of getting heads with your (potentially) biased coin.

As to your question about combining samples reducing error- if you flip the coin 100 times do you think you'll have a better or worse estimate than if you fip the coin 1000 times? 10000 times?

As to non-sampling errors, its hard to make a model with any kind of random-error that won't average out by aggregating the polls. However, systematic errors that are present across polls (imagine that 3/4 of the population of a state only spoke Lortax, an alien language, and that everyone who spoke Lortax were planning to vote not for Romney, or Obama, but for Kang. By not conducting polls in Lortax, every poll is systematically biased against Kang) won't cancel out, but they won't grow by including more polls.


I think the my cognitive problem was that the absolute error does actually grow, the relative error doesn't. So while the error in number of people grows, the percentage of error would shrink.

So what kind of windowing average do they use for the distribution? A loaded coin would have a consistent bias that the average would converge on. But for a signal that can't be modeled with an equation, you'd have to window the last N elections or something? And what about Reps that vote Obama or Dems that vote Romney? Is there a chain of Bayesian functions for the different demographics?

Feels like a lot of black magic to me, though that's consistent with me being confused I suppose.
 
  • #116
each (weekly) copy of the economist is purchased by about 750,000 americans, whereas each (daily) copy of the new york times is purchased by less than one million readers. so the economist has a rather large relative readership.
 
  • #117
CAC1001 said:
The U.S.'s was very high in the 1950s because of the tax increases that had been passed during the very left-leaning FDR.
The top fed rate stayed at 91% until 1964, with one Republican President and two Republican controlled Congresses during this period. I don't know enough about the history of this period to speak about whether or not there were efforts underway to lower rates. Maybe one reason the rate wasn't lowered was that (despite arguments to the contrary), it wasn't tanking the economy? In fact, GDP growth rate and unemployment were both pretty good, at about 5% in 1964.

Edit: This is a redundant argument that I just noticed has mostly been addressed in a previous post. Feel free to ignore.
 
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  • #118
So what kind of windowing average do they use for the distribution? A loaded coin would have a consistent bias that the average would converge on. But for a signal that can't be modeled with an equation, you'd have to window the last N elections or something? And what about Reps that vote Obama or Dems that vote Romney? Is there a chain of Bayesian functions for the different demographics?

I think you are overthinking things. The assumption made is that on any given day x% of the population will vote democrat, y% will vote Republican, a z% won't be decided yet.

Now, if I could call every single person in a state and ask them how they are going to vote, I'd know x, y and z with certainty. I can't do this, so instead I can call a few thousand people at random and ask them. Now I ask, what values for x are consistent with the answers I got when I called? So instead of a probability of getting heads when I flip a coin, I have a probability of getting "I'm voting for whoever" when I call a random person the phone.

This is the simplest polling, and requires nothing of the last few elections as an input. Its just attempting to suss out what's going right now.

Now, the simplest version of correcting for demographics goes like this- let's say I call 1000 people, and I find out that 82% of people are voting for X and (18% are voting for Y, no undecides). However, I realize that I've gotten unlucky in my sampling and 90% of the people I've called are women. Further, the way women and men are voting is very different- 90% of women are voting for X, but only 10% of the men!

Here, I might be tempted to correct for demographics- I'd say 'ok, I have estimates of how men and women vote, but my overall sample is not representative. So, I'm going to go ahead and say in the actual population only 50% are voting for X(0.50*0.10 (men) + 0.50*0.90(women)). Now- this correction DOES effect our sample error- I leave it to the interested reader to figure out how to set the sampling error- but the why is simple. We have a much smaller sample of men, so a larger error in this case.

A more difficult question, I imagine, is what to do if your sample comes back 40% democrat, 30% republican,30% independent, or something of that nature. The problem is that democrats are very likely to vote Obama, Republicans very likely to vote Romney, so correcting a demographic imbalance can end up making your poll worthless- if you always correct to nearly 50/50 dem/rep the vote is alway going to be nearly 50/50. Also, people probably switch between a party identification and independent at a whim. If you are a Republican live in San Francisco or NYC and expect democrats to dominate, you might be more likely to indentify as independent so you don't feel like you were on the losing side. Same thing for democrats in Houston,etc.

Now when we aggregate polls we have to be careful because people's opinions change over time, so we might only want to aggregate the most recent polls, or use some model to try and predict how people's opinions change,etc. We can, in principle, make it as complicated as we like, but the underlying idea is very simple.
 
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  • #119
Ah, then just weighting for demographics. I have even more issues trying to divide all humans up between males and females. You're right, I'm overthinking this, but it's hard to see the simplified explanation as being very representative. I'm not arguing that it isn't sufficient; it just strains my intuition.

Anyway, thanks for the discussion, I'm going to shut up now.
 
  • #120
I'm almost hoping that the election results in a http://news.yahoo.com/romney-biden-administration-could-happen-223736689--abc-news-politics.html administration. Then, perhaps the Democrats and Republicans would finally talk to each other.
 
  • #121
Borg said:
I'm almost hoping that the election results in a http://news.yahoo.com/romney-biden-administration-could-happen-223736689--abc-news-politics.html administration. Then, perhaps the Democrats and Republicans would finally talk to each other.

They talk to each other plenty... and exclude their mutually beneficial arrangements from discussion at debates.
 
  • #122
Borg said:
I'm almost hoping that the election results in a http://news.yahoo.com/romney-biden-administration-could-happen-223736689--abc-news-politics.html administration. Then, perhaps the Democrats and Republicans would finally talk to each other.

Why not an Obama-Ryan administration? It would be the fittest ticket ever.
 
  • #123
www.intrade.com


Barack Obama
69.8%
Today's Change: +4.0
Shares Traded: 3,389,793

Mitt Romney
30.4%
Today's Change: -4.0
Shares Traded: 2,908,623
 
  • #124
Two pundits prepared to stick their neck out and predict results in the swing states both foresee a win for Barack Obama. Larry Sabato's Crystal Ball gives Obama 290 electoral college votes - 20 more than the 270 required to win - while Nate Silver at the New York Times' FiveThirtyEight blog envisages Obama taking 307 votes.

There are conservative pundits who predict quite the opposite. One, Dick Morris, a former Democrat, foresees Mitt Romney picking up 325 electoral college votes. George Will of the Washington Post, puts Romney on 321. Meanwhile, from the liberal camp, Josh Marshall's Talking Points Memo puts Barack Obama on 303.

A handful of websites that choose not to predict a result in "toss-up" states see a small advantage for Obama. The New York Times and the Washington Post both think Obama is able to rely on at least 243 electoral college votes, compared with 206 for Mitt Romney. Charlie Cook gives Obama 237 to Romney's 191, while Real Clear Politics leaves a full 146 electoral college votes in the toss-up category, with Obama on 201, and Romney on 191.

http://www.bbc.co.uk/news/world-us-canada-20201713
 
  • #125
I'm picking Obama 291 - 248 (including Obama winning 1 electoral vote in NE).

I think maximum for Obama would be 333 - 226 if Obama sweeps every realistic 50-50 state.

I think maximum for Romney would be a 279-259 win if Romney sweeps every realistic 50-50 state.

Romney could win Ohio and still lose. He needs Ohio and either Colorado or New Hampshire (winning NH would create a tie, given a 4-1 split in NE). Granted, Romney has a better chance in CO and NH than OH, but there's no particular reason an OH victory means a CO/NH victory.
 
  • #126
I will go with the flow and predict Obama to win. :-p
 
  • #127
I think Obama is going to win, and I look forward to my dose of Schadenfreude the next day.
 
  • #128
Bob Dylan has predicted Obama in a landslide.
 
  • #130
A little boost towards Obama. Chrysler, whom Romney parroted Trump's false accusations about shipping jobs to China, is giving their entire workforce the day off to vote:

http://www.politico.com/politico44/2012/11/chrysler-gives-workers-day-off-to-vote-148617.html
 
  • #131
I believe Obama will win, with 300-310 votes in the electoral college.
 
  • #133
I went to the polls at 3pm and had a 45 minute wait for the first time ever. I always vote around that time because it's never busy. Everyone that I spoke with at work had to wait over an hour when they voted in the morning. Looks like it's going to be a big turnout in Virginia.
 
  • #134
More problems with voting. Cheating, this time.

http://www.rawstory.com/rs/2012/11/06/oregon-election-worker-fired-for-altering-ballots-to-republican-straight-ticket/#.UJkw3tO6X4k.reddit
 
  • #135
Pythagorean said:
More problems with voting. Cheating, this time.

http://www.rawstory.com/rs/2012/11/06/oregon-election-worker-fired-for-altering-ballots-to-republican-straight-ticket/#.UJkw3tO6X4k.reddit

She needs to lose her right to vote by becoming a convicted felon.
 
  • #136
nsaspook said:
She needs to lose her right to vote by becoming a convicted felon.
And then there should be a trial.
 
  • #137
Jimmy Snyder said:
And then there should be a trial.
I say we vote on it. You can count the votes.
 
  • #139
Looks like FL might be close (yes, I'm aware the panhandle votes will be solid red, but there's more uncounted Miami-Dade ballots than there are panhandle residents)! There's a non-trivial chance this might be an early night.

I'm curious about the people that chose Romney in the poll above this thread. What polling info were you folks basing your decision on?

PS: On a related note - since we don't have a thread for Congressional seats - the numbers for Scott Brown are not looking great. That's somewhat expected, but unfortunate.
 
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  • #141
With 78% of FL precincts reporting (and two-thirds of the uncounted ballots in Broward and Miami-Dade), I think Obama could win FL by over 1%.

Edit: Upon closer inspection, I think the margin will probably be under 1%, but still in Obama's favor.
 
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  • #142
Gokul43201 said:
With 78% of FL precincts reporting (and two-thirds of the uncounted ballots in Broward and Miami-Dade), I think Obama could win FL by over 1%.

Edit: Upon closer inspection, I think the margin will probably be a little under 1%, but still in Obama's favor.

Will there be a recount?
 
  • #143
does anyone have a link that shows all counts? i want to see if gary gets his 5%
 
  • #144
Greg Bernhardt said:
does anyone have a link that shows all counts? i want to see if gary gets his 5%

http://www.youtube.com/politics

US General Election
November 6, 2012
This page updates automatically
Candidate

Popular Vote

Electoral

Mitt
Romney

50.5%
20,654,439

153

Barack
Obama

48.5%
19,848,072

123

Gary
Johnson

0.6%
251,259

0
 
  • #145
Looks like the Tea Party just lost the Republicans a Senate seat in IN.

In FL, I think we'll get pretty close to triggering that automatic recount. The margin to beat is 0.5%.

Edit: The only pollster I know that called FL for Obama was Silver (his margin for Obama in FL was 0.3%).
 
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  • #148
Looks like the Tea Party just lost the Republicans a Senate seat in IN.

Also lost them a pickup in Missouri. Fascinating. The Republican Party needs to remove the word "rape" from its vocabulary.
 
  • #149
Obama seems to have taken PA quite easily (so NOT an expansion of the Republican territory after all), and is looking pretty comfortable in IA.
 
  • #150
right...

(comment out of context with removed post)
 
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