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Reasonable theories I have heard have included:

  • A change in polling foundations (home phones become cell phones = limitations on traditional cold calling... and also the shift into online polls). Plus perhaps the diminishing patience people have with enduring the polling process (I believe the percentage of people who agree to it has dropped consistently)

  • A hesitation/fear that keeps some people from admitting that they support a candidate who is being widely presented as detestable/deplorable in much of the public discussion/media. [apparently an effect common enough to have a term, see the Shy Tory Factor... the possibility it might be important was even presciently suggested in a question herehere a couple weeks ago]

  • A possible tendency for people to publicly show full support for minority/heroic candidates because it's the socially favorable thing to do, even when they're actually entertaining uncertainty internally. [this is along the lines of the Bradley Effect]

  • People failing to turn out as they've indicated they will... perhaps due to weather (though it's fairly unlikely this was a big factor in this election), a false sense of security (such as when the polls in the days leading up to and into election day suggest a comfortable victory!), or just a general failure to muster the effort/will to follow through with the voting.

Regardless, there is a widespread trend of polls failing recently, and maybe even specifically underestimating the conservative side. In 2015, the UK Parliament was projected to come out about even between the top two parties, but the conservatives won by over 5%, ending up with the majority (which was considered to be a near 0% chance possibility as the day began), this summer Brexit passed (considered almost certain to fail as the day began, ended up passing by 4%), and last month the Colombian Peace Referendum failed (after being consistently polled to pass by about 10%). So perhaps this is a trend to be aware of going forward until polling methods can hopefully adapt. Others here have also pointed out there was an underforecast conservative swing in the 2016 Iceland election and changes in the Swedish election.

Note, though, that most models showing the full spread of possibilities didn't say this was a set Clinton win, but that it leaned maybe 70-80% likely that Clinton would win.
A 1 out of 5 chance of being wrong is not insignificant...
If they say there's a 20% chance of rain today, you shouldn't be surprised if it does rain! In meteorology we've often got the same continuing struggles, particularly when it comes to issues like hurricane/storm forecasting; getting people to understand the uncertainty and full potentials of realistic possibilities. This is something we should keep on our media to better portray to us, and something school math courses could better focus on, perhaps being of significant benefit to a great many.

Considering that most polls have maybe a 4-6% typical error, this result was really quite within the range of possibility for most (although their consistent bias suggests that there really are some fundamental shortcomings). But, still, most of the quality election forecasters did also measure in some considerations of this trend towards less poll reliability, and were urging caution regarding overconfidence in the indicated spread (as Nate Silver of fivethirtyeight did here on election morning).

Reasonable theories I have heard have included:

  • A change in polling foundations (home phones become cell phones = limitations on traditional cold calling... and also the shift into online polls). Plus perhaps the diminishing patience people have with enduring the polling process (I believe the percentage of people who agree to it has dropped consistently)

  • A hesitation/fear that keeps some people from admitting that they support a candidate who is being widely presented as detestable/deplorable in much of the public discussion/media. [apparently an effect common enough to have a term, see the Shy Tory Factor... the possibility it might be important was even presciently suggested in a question here a couple weeks ago]

  • A possible tendency for people to publicly show full support for minority/heroic candidates because it's the socially favorable thing to do, even when they're actually entertaining uncertainty internally. [this is along the lines of the Bradley Effect]

  • People failing to turn out as they've indicated they will... perhaps due to weather (though it's fairly unlikely this was a big factor in this election), a false sense of security (such as when the polls in the days leading up to and into election day suggest a comfortable victory!), or just a general failure to muster the effort/will to follow through with the voting.

Regardless, there is a widespread trend of polls failing recently, and maybe even specifically underestimating the conservative side. In 2015, the UK Parliament was projected to come out about even between the top two parties, but the conservatives won by over 5%, ending up with the majority (which was considered to be a near 0% chance possibility as the day began), this summer Brexit passed (considered almost certain to fail as the day began, ended up passing by 4%), and last month the Colombian Peace Referendum failed (after being consistently polled to pass by about 10%). So perhaps this is a trend to be aware of going forward until polling methods can hopefully adapt. Others here have also pointed out there was an underforecast conservative swing in the 2016 Iceland election and changes in the Swedish election.

Note, though, that most models showing the full spread of possibilities didn't say this was a set Clinton win, but that it leaned maybe 70-80% likely that Clinton would win.
A 1 out of 5 chance of being wrong is not insignificant...
If they say there's a 20% chance of rain today, you shouldn't be surprised if it does rain! In meteorology we've often got the same continuing struggles, particularly when it comes to issues like hurricane/storm forecasting; getting people to understand the uncertainty and full potentials of realistic possibilities. This is something we should keep on our media to better portray to us, and something school math courses could better focus on, perhaps being of significant benefit to a great many.

Considering that most polls have maybe a 4-6% typical error, this result was really quite within the range of possibility for most (although their consistent bias suggests that there really are some fundamental shortcomings). But, still, most of the quality election forecasters did also measure in some considerations of this trend towards less poll reliability, and were urging caution regarding overconfidence in the indicated spread (as Nate Silver of fivethirtyeight did here on election morning).

Reasonable theories I have heard have included:

  • A change in polling foundations (home phones become cell phones = limitations on traditional cold calling... and also the shift into online polls). Plus perhaps the diminishing patience people have with enduring the polling process (I believe the percentage of people who agree to it has dropped consistently)

  • A hesitation/fear that keeps some people from admitting that they support a candidate who is being widely presented as detestable/deplorable in much of the public discussion/media. [apparently an effect common enough to have a term, see the Shy Tory Factor... the possibility it might be important was even presciently suggested in a question here a couple weeks ago]

  • A possible tendency for people to publicly show full support for minority/heroic candidates because it's the socially favorable thing to do, even when they're actually entertaining uncertainty internally. [this is along the lines of the Bradley Effect]

  • People failing to turn out as they've indicated they will... perhaps due to weather (though it's fairly unlikely this was a big factor in this election), a false sense of security (such as when the polls in the days leading up to and into election day suggest a comfortable victory!), or just a general failure to muster the effort/will to follow through with the voting.

Regardless, there is a widespread trend of polls failing recently, and maybe even specifically underestimating the conservative side. In 2015, the UK Parliament was projected to come out about even between the top two parties, but the conservatives won by over 5%, ending up with the majority (which was considered to be a near 0% chance possibility as the day began), this summer Brexit passed (considered almost certain to fail as the day began, ended up passing by 4%), and last month the Colombian Peace Referendum failed (after being consistently polled to pass by about 10%). So perhaps this is a trend to be aware of going forward until polling methods can hopefully adapt. Others here have also pointed out there was an underforecast conservative swing in the 2016 Iceland election and changes in the Swedish election.

Note, though, that most models showing the full spread of possibilities didn't say this was a set Clinton win, but that it leaned maybe 70-80% likely that Clinton would win.
A 1 out of 5 chance of being wrong is not insignificant...
If they say there's a 20% chance of rain today, you shouldn't be surprised if it does rain! In meteorology we've often got the same continuing struggles, particularly when it comes to issues like hurricane/storm forecasting; getting people to understand the uncertainty and full potentials of realistic possibilities. This is something we should keep on our media to better portray to us, and something school math courses could better focus on, perhaps being of significant benefit to a great many.

Considering that most polls have maybe a 4-6% typical error, this result was really quite within the range of possibility for most (although their consistent bias suggests that there really are some fundamental shortcomings). But, still, most of the quality election forecasters did also measure in some considerations of this trend towards less poll reliability, and were urging caution regarding overconfidence in the indicated spread (as Nate Silver of fivethirtyeight did here on election morning).

7 Replaced \ with / as appropriate in written English. Backslash is used almost exclusively in computer configuration files.
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Reasonable theories I have heard have included:

  • A change in polling foundations (home phones become cell phones = limitations on traditional cold calling... and also the shift into online polls). Plus perhaps the diminishing patience people have with enduring the polling process (I believe the percentage of people who agree to it has dropped consistently)

  • A hesitation\fearhesitation/fear that keeps some people from admitting that they support a candidate who is being widely presented as detestable\deplorabledetestable/deplorable in much of the public discussion\mediadiscussion/media. [apparently an effect common enough to have a term, see the Shy Tory Factor... the possibility it might be important was even presciently suggested in a question here a couple weeks ago]

  • A possible tendency for people to publicly show full support for minority\heroicminority/heroic candidates because it's the socially favorable thing to do, even when they're actually entertaining uncertainty internally. [this is along the lines of the Bradley Effect]

  • People failing to turn out as they've indicated they will... perhaps due to weather (though it's fairly unlikely this was a big factor in this election), a false sense of security (such as when the polls in the days leading up to and into election day suggest a comfortable victory!), or just a general failure to muster the effort\willeffort/will to follow through with the voting.

Regardless, there is a widespread trend of polls failing recently, and maybe even specifically underestimating the conservative side. In 2015, the UK Parliament was projected to come out about even between the top two parties, but the conservatives won by over 5%, ending up with the majority (which was considered to be a near 0% chance possibility as the day began), this summer Brexit passed (considered almost certain to fail as the day began, ended up passing by 4%), and last month the Colombian Peace Referendum failed (after being consistently polled to pass by about 10%). So perhaps this is a trend to be aware of going forward until polling methods can hopefully adapt. Others here have also pointed out there was an underforecast conservative swing in the 2016 Iceland election and changes in the Swedish election.

Note, though, that most models showing the full spread of possibilities didn't say this was a set Clinton win, but that it leaned maybe 70-80% likely that Clinton would win.
A 1 out of 5 chance of being wrong is not insignificant...
If they say there's a 20% chance of rain today, you shouldn't be surprised if it does rain! In meteorology we've often got the same continuing struggles, particularly when it comes to issues like hurricane\stormhurricane/storm forecasting; getting people to understand the uncertainty and full potentials of realistic possibilities. This is something we should keep on our media to better portray to us, and something school math courses could better focus on, perhaps being of significant benefit to a great many.

Considering that most polls have maybe a 4-6% typical error, this result was really quite within the range of possibility for most (although their consistent bias suggests that there really are some fundamental shortcomings). But, still, most of the quality election forecasters did also measure in some considerations of this trend towards less poll reliability, and were urging caution regarding overconfidence in the indicated spread (as Nate Silver of fivethirtyeight did here on election morning).

Reasonable theories I have heard have included:

  • A change in polling foundations (home phones become cell phones = limitations on traditional cold calling... and also the shift into online polls). Plus perhaps the diminishing patience people have with enduring the polling process (I believe the percentage of people who agree to it has dropped consistently)

  • A hesitation\fear that keeps some people from admitting that they support a candidate who is being widely presented as detestable\deplorable in much of the public discussion\media. [apparently an effect common enough to have a term, see the Shy Tory Factor... the possibility it might be important was even presciently suggested in a question here a couple weeks ago]

  • A possible tendency for people to publicly show full support for minority\heroic candidates because it's the socially favorable thing to do, even when they're actually entertaining uncertainty internally. [this is along the lines of the Bradley Effect]

  • People failing to turn out as they've indicated they will... perhaps due to weather (though it's fairly unlikely this was a big factor in this election), a false sense of security (such as when the polls in the days leading up to and into election day suggest a comfortable victory!), or just a general failure to muster the effort\will to follow through with the voting.

Regardless, there is a widespread trend of polls failing recently, and maybe even specifically underestimating the conservative side. In 2015, the UK Parliament was projected to come out about even between the top two parties, but the conservatives won by over 5%, ending up with the majority (which was considered to be a near 0% chance possibility as the day began), this summer Brexit passed (considered almost certain to fail as the day began, ended up passing by 4%), and last month the Colombian Peace Referendum failed (after being consistently polled to pass by about 10%). So perhaps this is a trend to be aware of going forward until polling methods can hopefully adapt. Others here have also pointed out there was an underforecast conservative swing in the 2016 Iceland election and changes in the Swedish election.

Note, though, that most models showing the full spread of possibilities didn't say this was a set Clinton win, but that it leaned maybe 70-80% likely that Clinton would win.
A 1 out of 5 chance of being wrong is not insignificant...
If they say there's a 20% chance of rain today, you shouldn't be surprised if it does rain! In meteorology we've often got the same continuing struggles, particularly when it comes to issues like hurricane\storm forecasting; getting people to understand the uncertainty and full potentials of realistic possibilities. This is something we should keep on our media to better portray to us, and something school math courses could better focus on, perhaps being of significant benefit to a great many.

Considering that most polls have maybe a 4-6% typical error, this result was really quite within the range of possibility for most (although their consistent bias suggests that there really are some fundamental shortcomings). But, still, most of the quality election forecasters did also measure in some considerations of this trend towards less poll reliability, and were urging caution regarding overconfidence in the indicated spread (as Nate Silver of fivethirtyeight did here on election morning).

Reasonable theories I have heard have included:

  • A change in polling foundations (home phones become cell phones = limitations on traditional cold calling... and also the shift into online polls). Plus perhaps the diminishing patience people have with enduring the polling process (I believe the percentage of people who agree to it has dropped consistently)

  • A hesitation/fear that keeps some people from admitting that they support a candidate who is being widely presented as detestable/deplorable in much of the public discussion/media. [apparently an effect common enough to have a term, see the Shy Tory Factor... the possibility it might be important was even presciently suggested in a question here a couple weeks ago]

  • A possible tendency for people to publicly show full support for minority/heroic candidates because it's the socially favorable thing to do, even when they're actually entertaining uncertainty internally. [this is along the lines of the Bradley Effect]

  • People failing to turn out as they've indicated they will... perhaps due to weather (though it's fairly unlikely this was a big factor in this election), a false sense of security (such as when the polls in the days leading up to and into election day suggest a comfortable victory!), or just a general failure to muster the effort/will to follow through with the voting.

Regardless, there is a widespread trend of polls failing recently, and maybe even specifically underestimating the conservative side. In 2015, the UK Parliament was projected to come out about even between the top two parties, but the conservatives won by over 5%, ending up with the majority (which was considered to be a near 0% chance possibility as the day began), this summer Brexit passed (considered almost certain to fail as the day began, ended up passing by 4%), and last month the Colombian Peace Referendum failed (after being consistently polled to pass by about 10%). So perhaps this is a trend to be aware of going forward until polling methods can hopefully adapt. Others here have also pointed out there was an underforecast conservative swing in the 2016 Iceland election and changes in the Swedish election.

Note, though, that most models showing the full spread of possibilities didn't say this was a set Clinton win, but that it leaned maybe 70-80% likely that Clinton would win.
A 1 out of 5 chance of being wrong is not insignificant...
If they say there's a 20% chance of rain today, you shouldn't be surprised if it does rain! In meteorology we've often got the same continuing struggles, particularly when it comes to issues like hurricane/storm forecasting; getting people to understand the uncertainty and full potentials of realistic possibilities. This is something we should keep on our media to better portray to us, and something school math courses could better focus on, perhaps being of significant benefit to a great many.

Considering that most polls have maybe a 4-6% typical error, this result was really quite within the range of possibility for most (although their consistent bias suggests that there really are some fundamental shortcomings). But, still, most of the quality election forecasters did also measure in some considerations of this trend towards less poll reliability, and were urging caution regarding overconfidence in the indicated spread (as Nate Silver of fivethirtyeight did here on election morning).

6 added 87 characters in body
source | link

Reasonable theories I have heard have included:

  • A change in polling foundationfoundations (home phones become cell phones = limitations on traditional cold calling... and also the changing use ofshift into online polls). Plus perhaps changingthe diminishing patience people have with enduring the polling process (I believe the percentage of people who agree to do it has dropped consistently)

  • A hesitation\fear that keeps some people from admitting that they support a candidate who is being widely presented as detestable\deplorable in much of the public discussion\media. [apparently an effect common enough to have a term, see the Shy Tory Factor... the possibility it might be important was even presciently suggested in a question here a couple weeks ago]

  • A possible tendency for people to publicly show full support for minority\heroic candidates because it's the socially favorable thing to do, even when they're actually entertaining uncertainty internally. [this is along the lines of the Bradley Effect]

  • People failing to turn out as they've indicated they will... perhaps due to weather (though this isit's fairly unlikely this was a big factor in this election), a false sense of security (such as when the polls in the days leading up to and into election day suggest a comfortable victory!), or just a general failure to muster the effort\will to follow through with the voting.

Regardless, there is a widespread trend of polls failing recently, and maybe even specifically underestimating the conservative side. In 2015, the UK Parliament was projected to come out about even between the top two parties, but the conservatives won by over 5%, ending up with the majority (considered nearwhich was considered to be a near 0% chance possibility as the day began), this summer Brexit passed (considered almost certain to fail as the day began, ended up passing by 4%), and last month the Colombian Peace Referendum failed (after being consistently polled to pass by about 10%). So perhaps this is a trend to be aware of going forward if\untiluntil polling methods can hopefully adapt. Others also here have also pointed out there was an underforecast conservative swing in the 2016 Iceland election and some changechanges in the Swedish election too.

Note, though, that most models showing the full spread of possibilitypossibilities didn't say this was a set Clinton win, but that it leaned maybe 70-80% likely that Clinton would win.
A 1 out of 5 chance of being wrong is not insignificant...
If they say there's a 20% chance of rain today, you shouldn't be surprised if it does rain! In meteorology we've often got the same continuing struggles, particularly when it comes to issues like hurricane\storm forecasting; getting people to understand the uncertainty and full potentials of reasonablerealistic possibilities. This is something we should keep on our media to better portray to us, and something school math courses could better focus on, perhaps being of significant benefit to a great many.

Considering that most polls have maybe a 4-6% typical error, this result was really quite within the range of possibility for most (although their consistent bias suggests that there really are some fundamental shortcomings). But, still, most of the quality election forecasters did also measure in some considerations of this trend totowards less poll reliability in polls, and were urging caution regarding overconfidence in the indicated spread (as Nate Silver of fivethirtyeight did here on election morning).

Reasonable theories I have heard have included:

  • A change in polling foundation (home phones become cell phones = limitations on traditional cold calling... and also the changing use of online polls). Plus perhaps changing patience people have with enduring the polling process (I believe the percentage of people who agree to do it has dropped consistently)

  • A hesitation\fear that keeps some people from admitting that they support a candidate who is being widely presented as detestable\deplorable in much of the public discussion\media. [apparently an effect common enough to have a term, see the Shy Tory Factor... the possibility was even presciently suggested in a question here a couple weeks ago]

  • A possible tendency for people to publicly show full support for minority\heroic candidates because it's the socially favorable thing to do, even when they're actually entertaining uncertainty internally. [this is along the lines of the Bradley Effect]

  • People failing to turn out as they've indicated they will... perhaps due to weather (though this is fairly unlikely in this election), a false sense of security (such as when the polls in the days leading up to and into election day suggest a comfortable victory!), or just a general failure to muster the effort\will to follow through with the voting.

Regardless, there is a widespread trend of polls failing recently, and maybe even specifically underestimating the conservative side. In 2015, the UK Parliament was projected to come out about even between the top two parties, but the conservatives won by over 5%, ending up with the majority (considered near a 0% chance possibility as the day began), this summer Brexit passed (considered almost certain to fail as the day began, ended up passing by 4%), and last month the Colombian Peace Referendum failed (after being consistently polled to pass by about 10%). So perhaps this is a trend to be aware of going forward if\until polling methods adapt. Others also here have pointed out there was an underforecast conservative swing in the 2016 Iceland election and some change in the Swedish election too.

Note, though, that most models showing the full spread of possibility didn't say this was a set Clinton win, but that it leaned maybe 70-80% likely that Clinton would win.
A 1 out of 5 chance of being wrong is not insignificant...
If they say there's a 20% chance of rain today, you shouldn't be surprised if it does rain! In meteorology we've often got the same continuing struggles, particularly when it comes to issues like hurricane\storm forecasting; getting people to understand the uncertainty and full potentials of reasonable possibilities. This is something we should keep on our media to better portray to us, and something school math courses could better focus on, perhaps being of significant benefit to a great many.

Considering that most polls have maybe a 4-6% typical error, this result was really quite within the range of possibility for most (although their consistent bias suggests that there really are some fundamental shortcomings). But, still, most of the quality election forecasters did measure in some considerations of this trend to less reliability in polls, and were urging caution regarding overconfidence in the indicated spread (as Nate Silver of fivethirtyeight did here).

Reasonable theories I have heard have included:

  • A change in polling foundations (home phones become cell phones = limitations on traditional cold calling... and also the shift into online polls). Plus perhaps the diminishing patience people have with enduring the polling process (I believe the percentage of people who agree to it has dropped consistently)

  • A hesitation\fear that keeps some people from admitting that they support a candidate who is being widely presented as detestable\deplorable in much of the public discussion\media. [apparently an effect common enough to have a term, see the Shy Tory Factor... the possibility it might be important was even presciently suggested in a question here a couple weeks ago]

  • A possible tendency for people to publicly show full support for minority\heroic candidates because it's the socially favorable thing to do, even when they're actually entertaining uncertainty internally. [this is along the lines of the Bradley Effect]

  • People failing to turn out as they've indicated they will... perhaps due to weather (though it's fairly unlikely this was a big factor in this election), a false sense of security (such as when the polls in the days leading up to and into election day suggest a comfortable victory!), or just a general failure to muster the effort\will to follow through with the voting.

Regardless, there is a widespread trend of polls failing recently, and maybe even specifically underestimating the conservative side. In 2015, the UK Parliament was projected to come out about even between the top two parties, but the conservatives won by over 5%, ending up with the majority (which was considered to be a near 0% chance possibility as the day began), this summer Brexit passed (considered almost certain to fail as the day began, ended up passing by 4%), and last month the Colombian Peace Referendum failed (after being consistently polled to pass by about 10%). So perhaps this is a trend to be aware of going forward until polling methods can hopefully adapt. Others here have also pointed out there was an underforecast conservative swing in the 2016 Iceland election and changes in the Swedish election.

Note, though, that most models showing the full spread of possibilities didn't say this was a set Clinton win, but that it leaned maybe 70-80% likely that Clinton would win.
A 1 out of 5 chance of being wrong is not insignificant...
If they say there's a 20% chance of rain today, you shouldn't be surprised if it does rain! In meteorology we've often got the same continuing struggles, particularly when it comes to issues like hurricane\storm forecasting; getting people to understand the uncertainty and full potentials of realistic possibilities. This is something we should keep on our media to better portray to us, and something school math courses could better focus on, perhaps being of significant benefit to a great many.

Considering that most polls have maybe a 4-6% typical error, this result was really quite within the range of possibility for most (although their consistent bias suggests that there really are some fundamental shortcomings). But, still, most of the quality election forecasters did also measure in some considerations of this trend towards less poll reliability, and were urging caution regarding overconfidence in the indicated spread (as Nate Silver of fivethirtyeight did here on election morning).

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