Why is the consensus that the Democrats are confident of overturning the house majority?

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I have seen numerous reports that describe how the Democrats are confident of overturning the house majority in the midterms. Where does this confidence spring from?










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    There isn't a definite answer to this so I expect this question to be closed, but here is an unbiased data-driven outline of why Democrats expect to retake the house - projects.fivethirtyeight.com/2018-midterm-election-forecast/…
    – Gramatik
    1 hour ago










  • Thank you for the link.
    – Ben
    1 hour ago










  • There must be specific, non-partisan reasons for the consensus - for example the nature of the voting system or public faux-pas?
    – Ben
    1 hour ago














up vote
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I have seen numerous reports that describe how the Democrats are confident of overturning the house majority in the midterms. Where does this confidence spring from?










share|improve this question

















  • 1




    There isn't a definite answer to this so I expect this question to be closed, but here is an unbiased data-driven outline of why Democrats expect to retake the house - projects.fivethirtyeight.com/2018-midterm-election-forecast/…
    – Gramatik
    1 hour ago










  • Thank you for the link.
    – Ben
    1 hour ago










  • There must be specific, non-partisan reasons for the consensus - for example the nature of the voting system or public faux-pas?
    – Ben
    1 hour ago












up vote
2
down vote

favorite









up vote
2
down vote

favorite











I have seen numerous reports that describe how the Democrats are confident of overturning the house majority in the midterms. Where does this confidence spring from?










share|improve this question













I have seen numerous reports that describe how the Democrats are confident of overturning the house majority in the midterms. Where does this confidence spring from?







united-states






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asked 1 hour ago









Ben

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  • 1




    There isn't a definite answer to this so I expect this question to be closed, but here is an unbiased data-driven outline of why Democrats expect to retake the house - projects.fivethirtyeight.com/2018-midterm-election-forecast/…
    – Gramatik
    1 hour ago










  • Thank you for the link.
    – Ben
    1 hour ago










  • There must be specific, non-partisan reasons for the consensus - for example the nature of the voting system or public faux-pas?
    – Ben
    1 hour ago












  • 1




    There isn't a definite answer to this so I expect this question to be closed, but here is an unbiased data-driven outline of why Democrats expect to retake the house - projects.fivethirtyeight.com/2018-midterm-election-forecast/…
    – Gramatik
    1 hour ago










  • Thank you for the link.
    – Ben
    1 hour ago










  • There must be specific, non-partisan reasons for the consensus - for example the nature of the voting system or public faux-pas?
    – Ben
    1 hour ago







1




1




There isn't a definite answer to this so I expect this question to be closed, but here is an unbiased data-driven outline of why Democrats expect to retake the house - projects.fivethirtyeight.com/2018-midterm-election-forecast/…
– Gramatik
1 hour ago




There isn't a definite answer to this so I expect this question to be closed, but here is an unbiased data-driven outline of why Democrats expect to retake the house - projects.fivethirtyeight.com/2018-midterm-election-forecast/…
– Gramatik
1 hour ago












Thank you for the link.
– Ben
1 hour ago




Thank you for the link.
– Ben
1 hour ago












There must be specific, non-partisan reasons for the consensus - for example the nature of the voting system or public faux-pas?
– Ben
1 hour ago




There must be specific, non-partisan reasons for the consensus - for example the nature of the voting system or public faux-pas?
– Ben
1 hour ago










2 Answers
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Polling data -- which is what is being analyzed by organizations like FiveThirtyEight -- indicates that Democrats are likely to win a majority in the House of Representatives. Polling data is the best and most objective way to predict the outcome.



However, there is no certainty. FiveThirtyEight gives Republicans a >12% chance of keeping the House. That's because polls have both random errors and potentially systematic errors. So no one is taking the outcome as a given. Polling data is imperfect, but it's the best we have.




Regarding the comparison to the 2016 presidential election: Polls generally put Clinton ahead of Trump, but only just. In the end Trump ended up winning very narrowly (indeed he lost the popular vote by a considerable margin). This is not really a "debacle" as some put it, as it was within the usual margin of error of the polls. Ultimately, it was a close race.



Before the election, FiveThirtyEight gave Trump a >25% chance of winning. Also, here is an article from 4 days before the 2016 election in which FiveThirtyEight discusses how close the polls are.



So, in 2016, we saw again that the polls are not perfect, but they did show it was close and they still are the best we have.






share|improve this answer


















  • 3




    @Ben: What you call a debacle statisticians call a normal result. Besides, polling mechanisms are never really at fault, since it's more with how polls are interpreted and whether interpreters are able to account for a poll's unavoidable inaccuracy/bias.
    – Giter
    1 hour ago







  • 1




    @Ben There isn't really a way to correct for that. The problem, as far as I'm aware, is that the citizenry was so polarized against Trump that people were uncomfortable admitting to a pollster that they were going to vote for Trump. Therefore, it was "clear" that Hillary voters outnumbered Trump voters and Hillary would win. In reality, the issue was that Trump voters were simply not honest with the pollsters, which skewed the data. The "correction" would be to weigh the results in one direction or another, which could be just as disastrous.
    – Ertai87
    1 hour ago






  • 1




    I'd like to know the justification for these two statements being correlated: "Polls generally put Clinton ahead of Trump, but only just", and "FiveThirtyEight gave Trump a >25% chance of winning". According to the evidence presented, on Nov. 7, FiveThirtyEight gave Trump a 30% chance of winning, Clinton a 70% chance. That's a gap of 40%; the gap in the chance of willing is greater than Trump's chance of winning at all! I'm not sure I'd qualify that as "just"...
    – Ertai87
    40 mins ago






  • 2




    @Ertai87 The gap of their chance of winning is not the same as the size of the gap in % of people voting for each, they are completely different percentages. If instead FiveThirtyEight predicted Clinton would get 70% of the total vote then indeed those models would have been very very very wrong. That wasn't the case.
    – Bryan Krause
    33 mins ago






  • 1




    In 2016, most forecasts assumed that Trump's chances of winning certain swing states were independent of each other. As a simple example, if Trump had a 30% chance of winning Ohio and a 30% chance of winning Michigan, then he had only a 9% chance of winning both. However, this ignores the fact that whatever circumstances would lead to him winning one state would equally apply to his chances of winning the other. FiveThirtyEight, I vaguely recall, made a mention of this in upgrading Trump's chances.
    – chepner
    3 mins ago

















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2
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The same place as always: There is no better indicator of how people will vote than how people tell you they will vote.



That said, on Nov 7, 2016 (or, to be more specific, the most recent data as of Nov. 7, because I know how this site likes specific data XD) most polls showed a clear majority for Hillary Clinton, and we all know how that one turned out. Polling isn't what it once was.






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Ertai87 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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    To be fair, Clinton did win a majority of votes. But they were clustered in such a way that she didn't get enough states. The polls were as accurate as normal, but looking at the country as a whole was misleading.
    – Bobson
    1 hour ago






  • 3




    Also, statisticians using aggregations of polls that included correlated polling errors, like FiveThirtyEight, gave Trump something like a 30% chance of winning (I forget the exact numbers) at the time of the election. Statistically, 30% chances occur pretty often...something like 30% of the time I think? It's hard to estimate the correctness of poll-based models to predict elections based on a single event, because having an event with a 30% probability occur doesn't give a ton of evidence against the model. Having the event occur 30 times would, but individual elections happen once.
    – Bryan Krause
    1 hour ago






  • 1




    Polls directly preceding the election projected a +3.2 advantage for Clinton, who won the actual popular vote by +2.1. That is an error of 1.1 points. The stated margin of error of each individual poll was between 2.3 and 4.5. Taking the average of 10 of these polls would probably produce a lower margin of error, somewhere around 1.5 points. Most individual polls were also within their margins of error, but some were slightly outside (Reuters, NBC, Monmouth, LA Times). The average of all polls was pretty accurate, and this attack on polling is unwarranted.
    – John
    56 mins ago






  • 2




    "Polling isn't what it once was", if you think the entire concept of polling has fallen on hard times because a single likely outcome didn't occur, I don't recommend a career in statistics (or gambling).
    – Giter
    55 mins ago







  • 1




    @Ertai87 I think your understanding of the statistics here are incorrect are are not the way that a statistician would describe it. The probabilities are based on the model. Given the model, 30% of the time Result A happens, 70% of the time result B happens. If result B happens, you might use that result to adjust the model in the future, but it gives you limited evidence that the model itself is flawed. Rather, it reflects the fact that the data you used to make predictions in the model were not perfect (and never can be). There is a difference between a wrong model and wrong prediction.
    – Bryan Krause
    37 mins ago










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2 Answers
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Polling data -- which is what is being analyzed by organizations like FiveThirtyEight -- indicates that Democrats are likely to win a majority in the House of Representatives. Polling data is the best and most objective way to predict the outcome.



However, there is no certainty. FiveThirtyEight gives Republicans a >12% chance of keeping the House. That's because polls have both random errors and potentially systematic errors. So no one is taking the outcome as a given. Polling data is imperfect, but it's the best we have.




Regarding the comparison to the 2016 presidential election: Polls generally put Clinton ahead of Trump, but only just. In the end Trump ended up winning very narrowly (indeed he lost the popular vote by a considerable margin). This is not really a "debacle" as some put it, as it was within the usual margin of error of the polls. Ultimately, it was a close race.



Before the election, FiveThirtyEight gave Trump a >25% chance of winning. Also, here is an article from 4 days before the 2016 election in which FiveThirtyEight discusses how close the polls are.



So, in 2016, we saw again that the polls are not perfect, but they did show it was close and they still are the best we have.






share|improve this answer


















  • 3




    @Ben: What you call a debacle statisticians call a normal result. Besides, polling mechanisms are never really at fault, since it's more with how polls are interpreted and whether interpreters are able to account for a poll's unavoidable inaccuracy/bias.
    – Giter
    1 hour ago







  • 1




    @Ben There isn't really a way to correct for that. The problem, as far as I'm aware, is that the citizenry was so polarized against Trump that people were uncomfortable admitting to a pollster that they were going to vote for Trump. Therefore, it was "clear" that Hillary voters outnumbered Trump voters and Hillary would win. In reality, the issue was that Trump voters were simply not honest with the pollsters, which skewed the data. The "correction" would be to weigh the results in one direction or another, which could be just as disastrous.
    – Ertai87
    1 hour ago






  • 1




    I'd like to know the justification for these two statements being correlated: "Polls generally put Clinton ahead of Trump, but only just", and "FiveThirtyEight gave Trump a >25% chance of winning". According to the evidence presented, on Nov. 7, FiveThirtyEight gave Trump a 30% chance of winning, Clinton a 70% chance. That's a gap of 40%; the gap in the chance of willing is greater than Trump's chance of winning at all! I'm not sure I'd qualify that as "just"...
    – Ertai87
    40 mins ago






  • 2




    @Ertai87 The gap of their chance of winning is not the same as the size of the gap in % of people voting for each, they are completely different percentages. If instead FiveThirtyEight predicted Clinton would get 70% of the total vote then indeed those models would have been very very very wrong. That wasn't the case.
    – Bryan Krause
    33 mins ago






  • 1




    In 2016, most forecasts assumed that Trump's chances of winning certain swing states were independent of each other. As a simple example, if Trump had a 30% chance of winning Ohio and a 30% chance of winning Michigan, then he had only a 9% chance of winning both. However, this ignores the fact that whatever circumstances would lead to him winning one state would equally apply to his chances of winning the other. FiveThirtyEight, I vaguely recall, made a mention of this in upgrading Trump's chances.
    – chepner
    3 mins ago














up vote
4
down vote













Polling data -- which is what is being analyzed by organizations like FiveThirtyEight -- indicates that Democrats are likely to win a majority in the House of Representatives. Polling data is the best and most objective way to predict the outcome.



However, there is no certainty. FiveThirtyEight gives Republicans a >12% chance of keeping the House. That's because polls have both random errors and potentially systematic errors. So no one is taking the outcome as a given. Polling data is imperfect, but it's the best we have.




Regarding the comparison to the 2016 presidential election: Polls generally put Clinton ahead of Trump, but only just. In the end Trump ended up winning very narrowly (indeed he lost the popular vote by a considerable margin). This is not really a "debacle" as some put it, as it was within the usual margin of error of the polls. Ultimately, it was a close race.



Before the election, FiveThirtyEight gave Trump a >25% chance of winning. Also, here is an article from 4 days before the 2016 election in which FiveThirtyEight discusses how close the polls are.



So, in 2016, we saw again that the polls are not perfect, but they did show it was close and they still are the best we have.






share|improve this answer


















  • 3




    @Ben: What you call a debacle statisticians call a normal result. Besides, polling mechanisms are never really at fault, since it's more with how polls are interpreted and whether interpreters are able to account for a poll's unavoidable inaccuracy/bias.
    – Giter
    1 hour ago







  • 1




    @Ben There isn't really a way to correct for that. The problem, as far as I'm aware, is that the citizenry was so polarized against Trump that people were uncomfortable admitting to a pollster that they were going to vote for Trump. Therefore, it was "clear" that Hillary voters outnumbered Trump voters and Hillary would win. In reality, the issue was that Trump voters were simply not honest with the pollsters, which skewed the data. The "correction" would be to weigh the results in one direction or another, which could be just as disastrous.
    – Ertai87
    1 hour ago






  • 1




    I'd like to know the justification for these two statements being correlated: "Polls generally put Clinton ahead of Trump, but only just", and "FiveThirtyEight gave Trump a >25% chance of winning". According to the evidence presented, on Nov. 7, FiveThirtyEight gave Trump a 30% chance of winning, Clinton a 70% chance. That's a gap of 40%; the gap in the chance of willing is greater than Trump's chance of winning at all! I'm not sure I'd qualify that as "just"...
    – Ertai87
    40 mins ago






  • 2




    @Ertai87 The gap of their chance of winning is not the same as the size of the gap in % of people voting for each, they are completely different percentages. If instead FiveThirtyEight predicted Clinton would get 70% of the total vote then indeed those models would have been very very very wrong. That wasn't the case.
    – Bryan Krause
    33 mins ago






  • 1




    In 2016, most forecasts assumed that Trump's chances of winning certain swing states were independent of each other. As a simple example, if Trump had a 30% chance of winning Ohio and a 30% chance of winning Michigan, then he had only a 9% chance of winning both. However, this ignores the fact that whatever circumstances would lead to him winning one state would equally apply to his chances of winning the other. FiveThirtyEight, I vaguely recall, made a mention of this in upgrading Trump's chances.
    – chepner
    3 mins ago












up vote
4
down vote










up vote
4
down vote









Polling data -- which is what is being analyzed by organizations like FiveThirtyEight -- indicates that Democrats are likely to win a majority in the House of Representatives. Polling data is the best and most objective way to predict the outcome.



However, there is no certainty. FiveThirtyEight gives Republicans a >12% chance of keeping the House. That's because polls have both random errors and potentially systematic errors. So no one is taking the outcome as a given. Polling data is imperfect, but it's the best we have.




Regarding the comparison to the 2016 presidential election: Polls generally put Clinton ahead of Trump, but only just. In the end Trump ended up winning very narrowly (indeed he lost the popular vote by a considerable margin). This is not really a "debacle" as some put it, as it was within the usual margin of error of the polls. Ultimately, it was a close race.



Before the election, FiveThirtyEight gave Trump a >25% chance of winning. Also, here is an article from 4 days before the 2016 election in which FiveThirtyEight discusses how close the polls are.



So, in 2016, we saw again that the polls are not perfect, but they did show it was close and they still are the best we have.






share|improve this answer














Polling data -- which is what is being analyzed by organizations like FiveThirtyEight -- indicates that Democrats are likely to win a majority in the House of Representatives. Polling data is the best and most objective way to predict the outcome.



However, there is no certainty. FiveThirtyEight gives Republicans a >12% chance of keeping the House. That's because polls have both random errors and potentially systematic errors. So no one is taking the outcome as a given. Polling data is imperfect, but it's the best we have.




Regarding the comparison to the 2016 presidential election: Polls generally put Clinton ahead of Trump, but only just. In the end Trump ended up winning very narrowly (indeed he lost the popular vote by a considerable margin). This is not really a "debacle" as some put it, as it was within the usual margin of error of the polls. Ultimately, it was a close race.



Before the election, FiveThirtyEight gave Trump a >25% chance of winning. Also, here is an article from 4 days before the 2016 election in which FiveThirtyEight discusses how close the polls are.



So, in 2016, we saw again that the polls are not perfect, but they did show it was close and they still are the best we have.







share|improve this answer














share|improve this answer



share|improve this answer








edited 53 mins ago

























answered 1 hour ago









Thomas

1805




1805







  • 3




    @Ben: What you call a debacle statisticians call a normal result. Besides, polling mechanisms are never really at fault, since it's more with how polls are interpreted and whether interpreters are able to account for a poll's unavoidable inaccuracy/bias.
    – Giter
    1 hour ago







  • 1




    @Ben There isn't really a way to correct for that. The problem, as far as I'm aware, is that the citizenry was so polarized against Trump that people were uncomfortable admitting to a pollster that they were going to vote for Trump. Therefore, it was "clear" that Hillary voters outnumbered Trump voters and Hillary would win. In reality, the issue was that Trump voters were simply not honest with the pollsters, which skewed the data. The "correction" would be to weigh the results in one direction or another, which could be just as disastrous.
    – Ertai87
    1 hour ago






  • 1




    I'd like to know the justification for these two statements being correlated: "Polls generally put Clinton ahead of Trump, but only just", and "FiveThirtyEight gave Trump a >25% chance of winning". According to the evidence presented, on Nov. 7, FiveThirtyEight gave Trump a 30% chance of winning, Clinton a 70% chance. That's a gap of 40%; the gap in the chance of willing is greater than Trump's chance of winning at all! I'm not sure I'd qualify that as "just"...
    – Ertai87
    40 mins ago






  • 2




    @Ertai87 The gap of their chance of winning is not the same as the size of the gap in % of people voting for each, they are completely different percentages. If instead FiveThirtyEight predicted Clinton would get 70% of the total vote then indeed those models would have been very very very wrong. That wasn't the case.
    – Bryan Krause
    33 mins ago






  • 1




    In 2016, most forecasts assumed that Trump's chances of winning certain swing states were independent of each other. As a simple example, if Trump had a 30% chance of winning Ohio and a 30% chance of winning Michigan, then he had only a 9% chance of winning both. However, this ignores the fact that whatever circumstances would lead to him winning one state would equally apply to his chances of winning the other. FiveThirtyEight, I vaguely recall, made a mention of this in upgrading Trump's chances.
    – chepner
    3 mins ago












  • 3




    @Ben: What you call a debacle statisticians call a normal result. Besides, polling mechanisms are never really at fault, since it's more with how polls are interpreted and whether interpreters are able to account for a poll's unavoidable inaccuracy/bias.
    – Giter
    1 hour ago







  • 1




    @Ben There isn't really a way to correct for that. The problem, as far as I'm aware, is that the citizenry was so polarized against Trump that people were uncomfortable admitting to a pollster that they were going to vote for Trump. Therefore, it was "clear" that Hillary voters outnumbered Trump voters and Hillary would win. In reality, the issue was that Trump voters were simply not honest with the pollsters, which skewed the data. The "correction" would be to weigh the results in one direction or another, which could be just as disastrous.
    – Ertai87
    1 hour ago






  • 1




    I'd like to know the justification for these two statements being correlated: "Polls generally put Clinton ahead of Trump, but only just", and "FiveThirtyEight gave Trump a >25% chance of winning". According to the evidence presented, on Nov. 7, FiveThirtyEight gave Trump a 30% chance of winning, Clinton a 70% chance. That's a gap of 40%; the gap in the chance of willing is greater than Trump's chance of winning at all! I'm not sure I'd qualify that as "just"...
    – Ertai87
    40 mins ago






  • 2




    @Ertai87 The gap of their chance of winning is not the same as the size of the gap in % of people voting for each, they are completely different percentages. If instead FiveThirtyEight predicted Clinton would get 70% of the total vote then indeed those models would have been very very very wrong. That wasn't the case.
    – Bryan Krause
    33 mins ago






  • 1




    In 2016, most forecasts assumed that Trump's chances of winning certain swing states were independent of each other. As a simple example, if Trump had a 30% chance of winning Ohio and a 30% chance of winning Michigan, then he had only a 9% chance of winning both. However, this ignores the fact that whatever circumstances would lead to him winning one state would equally apply to his chances of winning the other. FiveThirtyEight, I vaguely recall, made a mention of this in upgrading Trump's chances.
    – chepner
    3 mins ago







3




3




@Ben: What you call a debacle statisticians call a normal result. Besides, polling mechanisms are never really at fault, since it's more with how polls are interpreted and whether interpreters are able to account for a poll's unavoidable inaccuracy/bias.
– Giter
1 hour ago





@Ben: What you call a debacle statisticians call a normal result. Besides, polling mechanisms are never really at fault, since it's more with how polls are interpreted and whether interpreters are able to account for a poll's unavoidable inaccuracy/bias.
– Giter
1 hour ago





1




1




@Ben There isn't really a way to correct for that. The problem, as far as I'm aware, is that the citizenry was so polarized against Trump that people were uncomfortable admitting to a pollster that they were going to vote for Trump. Therefore, it was "clear" that Hillary voters outnumbered Trump voters and Hillary would win. In reality, the issue was that Trump voters were simply not honest with the pollsters, which skewed the data. The "correction" would be to weigh the results in one direction or another, which could be just as disastrous.
– Ertai87
1 hour ago




@Ben There isn't really a way to correct for that. The problem, as far as I'm aware, is that the citizenry was so polarized against Trump that people were uncomfortable admitting to a pollster that they were going to vote for Trump. Therefore, it was "clear" that Hillary voters outnumbered Trump voters and Hillary would win. In reality, the issue was that Trump voters were simply not honest with the pollsters, which skewed the data. The "correction" would be to weigh the results in one direction or another, which could be just as disastrous.
– Ertai87
1 hour ago




1




1




I'd like to know the justification for these two statements being correlated: "Polls generally put Clinton ahead of Trump, but only just", and "FiveThirtyEight gave Trump a >25% chance of winning". According to the evidence presented, on Nov. 7, FiveThirtyEight gave Trump a 30% chance of winning, Clinton a 70% chance. That's a gap of 40%; the gap in the chance of willing is greater than Trump's chance of winning at all! I'm not sure I'd qualify that as "just"...
– Ertai87
40 mins ago




I'd like to know the justification for these two statements being correlated: "Polls generally put Clinton ahead of Trump, but only just", and "FiveThirtyEight gave Trump a >25% chance of winning". According to the evidence presented, on Nov. 7, FiveThirtyEight gave Trump a 30% chance of winning, Clinton a 70% chance. That's a gap of 40%; the gap in the chance of willing is greater than Trump's chance of winning at all! I'm not sure I'd qualify that as "just"...
– Ertai87
40 mins ago




2




2




@Ertai87 The gap of their chance of winning is not the same as the size of the gap in % of people voting for each, they are completely different percentages. If instead FiveThirtyEight predicted Clinton would get 70% of the total vote then indeed those models would have been very very very wrong. That wasn't the case.
– Bryan Krause
33 mins ago




@Ertai87 The gap of their chance of winning is not the same as the size of the gap in % of people voting for each, they are completely different percentages. If instead FiveThirtyEight predicted Clinton would get 70% of the total vote then indeed those models would have been very very very wrong. That wasn't the case.
– Bryan Krause
33 mins ago




1




1




In 2016, most forecasts assumed that Trump's chances of winning certain swing states were independent of each other. As a simple example, if Trump had a 30% chance of winning Ohio and a 30% chance of winning Michigan, then he had only a 9% chance of winning both. However, this ignores the fact that whatever circumstances would lead to him winning one state would equally apply to his chances of winning the other. FiveThirtyEight, I vaguely recall, made a mention of this in upgrading Trump's chances.
– chepner
3 mins ago




In 2016, most forecasts assumed that Trump's chances of winning certain swing states were independent of each other. As a simple example, if Trump had a 30% chance of winning Ohio and a 30% chance of winning Michigan, then he had only a 9% chance of winning both. However, this ignores the fact that whatever circumstances would lead to him winning one state would equally apply to his chances of winning the other. FiveThirtyEight, I vaguely recall, made a mention of this in upgrading Trump's chances.
– chepner
3 mins ago










up vote
2
down vote













The same place as always: There is no better indicator of how people will vote than how people tell you they will vote.



That said, on Nov 7, 2016 (or, to be more specific, the most recent data as of Nov. 7, because I know how this site likes specific data XD) most polls showed a clear majority for Hillary Clinton, and we all know how that one turned out. Polling isn't what it once was.






share|improve this answer








New contributor




Ertai87 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.













  • 1




    To be fair, Clinton did win a majority of votes. But they were clustered in such a way that she didn't get enough states. The polls were as accurate as normal, but looking at the country as a whole was misleading.
    – Bobson
    1 hour ago






  • 3




    Also, statisticians using aggregations of polls that included correlated polling errors, like FiveThirtyEight, gave Trump something like a 30% chance of winning (I forget the exact numbers) at the time of the election. Statistically, 30% chances occur pretty often...something like 30% of the time I think? It's hard to estimate the correctness of poll-based models to predict elections based on a single event, because having an event with a 30% probability occur doesn't give a ton of evidence against the model. Having the event occur 30 times would, but individual elections happen once.
    – Bryan Krause
    1 hour ago






  • 1




    Polls directly preceding the election projected a +3.2 advantage for Clinton, who won the actual popular vote by +2.1. That is an error of 1.1 points. The stated margin of error of each individual poll was between 2.3 and 4.5. Taking the average of 10 of these polls would probably produce a lower margin of error, somewhere around 1.5 points. Most individual polls were also within their margins of error, but some were slightly outside (Reuters, NBC, Monmouth, LA Times). The average of all polls was pretty accurate, and this attack on polling is unwarranted.
    – John
    56 mins ago






  • 2




    "Polling isn't what it once was", if you think the entire concept of polling has fallen on hard times because a single likely outcome didn't occur, I don't recommend a career in statistics (or gambling).
    – Giter
    55 mins ago







  • 1




    @Ertai87 I think your understanding of the statistics here are incorrect are are not the way that a statistician would describe it. The probabilities are based on the model. Given the model, 30% of the time Result A happens, 70% of the time result B happens. If result B happens, you might use that result to adjust the model in the future, but it gives you limited evidence that the model itself is flawed. Rather, it reflects the fact that the data you used to make predictions in the model were not perfect (and never can be). There is a difference between a wrong model and wrong prediction.
    – Bryan Krause
    37 mins ago














up vote
2
down vote













The same place as always: There is no better indicator of how people will vote than how people tell you they will vote.



That said, on Nov 7, 2016 (or, to be more specific, the most recent data as of Nov. 7, because I know how this site likes specific data XD) most polls showed a clear majority for Hillary Clinton, and we all know how that one turned out. Polling isn't what it once was.






share|improve this answer








New contributor




Ertai87 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.













  • 1




    To be fair, Clinton did win a majority of votes. But they were clustered in such a way that she didn't get enough states. The polls were as accurate as normal, but looking at the country as a whole was misleading.
    – Bobson
    1 hour ago






  • 3




    Also, statisticians using aggregations of polls that included correlated polling errors, like FiveThirtyEight, gave Trump something like a 30% chance of winning (I forget the exact numbers) at the time of the election. Statistically, 30% chances occur pretty often...something like 30% of the time I think? It's hard to estimate the correctness of poll-based models to predict elections based on a single event, because having an event with a 30% probability occur doesn't give a ton of evidence against the model. Having the event occur 30 times would, but individual elections happen once.
    – Bryan Krause
    1 hour ago






  • 1




    Polls directly preceding the election projected a +3.2 advantage for Clinton, who won the actual popular vote by +2.1. That is an error of 1.1 points. The stated margin of error of each individual poll was between 2.3 and 4.5. Taking the average of 10 of these polls would probably produce a lower margin of error, somewhere around 1.5 points. Most individual polls were also within their margins of error, but some were slightly outside (Reuters, NBC, Monmouth, LA Times). The average of all polls was pretty accurate, and this attack on polling is unwarranted.
    – John
    56 mins ago






  • 2




    "Polling isn't what it once was", if you think the entire concept of polling has fallen on hard times because a single likely outcome didn't occur, I don't recommend a career in statistics (or gambling).
    – Giter
    55 mins ago







  • 1




    @Ertai87 I think your understanding of the statistics here are incorrect are are not the way that a statistician would describe it. The probabilities are based on the model. Given the model, 30% of the time Result A happens, 70% of the time result B happens. If result B happens, you might use that result to adjust the model in the future, but it gives you limited evidence that the model itself is flawed. Rather, it reflects the fact that the data you used to make predictions in the model were not perfect (and never can be). There is a difference between a wrong model and wrong prediction.
    – Bryan Krause
    37 mins ago












up vote
2
down vote










up vote
2
down vote









The same place as always: There is no better indicator of how people will vote than how people tell you they will vote.



That said, on Nov 7, 2016 (or, to be more specific, the most recent data as of Nov. 7, because I know how this site likes specific data XD) most polls showed a clear majority for Hillary Clinton, and we all know how that one turned out. Polling isn't what it once was.






share|improve this answer








New contributor




Ertai87 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.









The same place as always: There is no better indicator of how people will vote than how people tell you they will vote.



That said, on Nov 7, 2016 (or, to be more specific, the most recent data as of Nov. 7, because I know how this site likes specific data XD) most polls showed a clear majority for Hillary Clinton, and we all know how that one turned out. Polling isn't what it once was.







share|improve this answer








New contributor




Ertai87 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.









share|improve this answer



share|improve this answer






New contributor




Ertai87 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.









answered 1 hour ago









Ertai87

1292




1292




New contributor




Ertai87 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.





New contributor





Ertai87 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.






Ertai87 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.







  • 1




    To be fair, Clinton did win a majority of votes. But they were clustered in such a way that she didn't get enough states. The polls were as accurate as normal, but looking at the country as a whole was misleading.
    – Bobson
    1 hour ago






  • 3




    Also, statisticians using aggregations of polls that included correlated polling errors, like FiveThirtyEight, gave Trump something like a 30% chance of winning (I forget the exact numbers) at the time of the election. Statistically, 30% chances occur pretty often...something like 30% of the time I think? It's hard to estimate the correctness of poll-based models to predict elections based on a single event, because having an event with a 30% probability occur doesn't give a ton of evidence against the model. Having the event occur 30 times would, but individual elections happen once.
    – Bryan Krause
    1 hour ago






  • 1




    Polls directly preceding the election projected a +3.2 advantage for Clinton, who won the actual popular vote by +2.1. That is an error of 1.1 points. The stated margin of error of each individual poll was between 2.3 and 4.5. Taking the average of 10 of these polls would probably produce a lower margin of error, somewhere around 1.5 points. Most individual polls were also within their margins of error, but some were slightly outside (Reuters, NBC, Monmouth, LA Times). The average of all polls was pretty accurate, and this attack on polling is unwarranted.
    – John
    56 mins ago






  • 2




    "Polling isn't what it once was", if you think the entire concept of polling has fallen on hard times because a single likely outcome didn't occur, I don't recommend a career in statistics (or gambling).
    – Giter
    55 mins ago







  • 1




    @Ertai87 I think your understanding of the statistics here are incorrect are are not the way that a statistician would describe it. The probabilities are based on the model. Given the model, 30% of the time Result A happens, 70% of the time result B happens. If result B happens, you might use that result to adjust the model in the future, but it gives you limited evidence that the model itself is flawed. Rather, it reflects the fact that the data you used to make predictions in the model were not perfect (and never can be). There is a difference between a wrong model and wrong prediction.
    – Bryan Krause
    37 mins ago












  • 1




    To be fair, Clinton did win a majority of votes. But they were clustered in such a way that she didn't get enough states. The polls were as accurate as normal, but looking at the country as a whole was misleading.
    – Bobson
    1 hour ago






  • 3




    Also, statisticians using aggregations of polls that included correlated polling errors, like FiveThirtyEight, gave Trump something like a 30% chance of winning (I forget the exact numbers) at the time of the election. Statistically, 30% chances occur pretty often...something like 30% of the time I think? It's hard to estimate the correctness of poll-based models to predict elections based on a single event, because having an event with a 30% probability occur doesn't give a ton of evidence against the model. Having the event occur 30 times would, but individual elections happen once.
    – Bryan Krause
    1 hour ago






  • 1




    Polls directly preceding the election projected a +3.2 advantage for Clinton, who won the actual popular vote by +2.1. That is an error of 1.1 points. The stated margin of error of each individual poll was between 2.3 and 4.5. Taking the average of 10 of these polls would probably produce a lower margin of error, somewhere around 1.5 points. Most individual polls were also within their margins of error, but some were slightly outside (Reuters, NBC, Monmouth, LA Times). The average of all polls was pretty accurate, and this attack on polling is unwarranted.
    – John
    56 mins ago






  • 2




    "Polling isn't what it once was", if you think the entire concept of polling has fallen on hard times because a single likely outcome didn't occur, I don't recommend a career in statistics (or gambling).
    – Giter
    55 mins ago







  • 1




    @Ertai87 I think your understanding of the statistics here are incorrect are are not the way that a statistician would describe it. The probabilities are based on the model. Given the model, 30% of the time Result A happens, 70% of the time result B happens. If result B happens, you might use that result to adjust the model in the future, but it gives you limited evidence that the model itself is flawed. Rather, it reflects the fact that the data you used to make predictions in the model were not perfect (and never can be). There is a difference between a wrong model and wrong prediction.
    – Bryan Krause
    37 mins ago







1




1




To be fair, Clinton did win a majority of votes. But they were clustered in such a way that she didn't get enough states. The polls were as accurate as normal, but looking at the country as a whole was misleading.
– Bobson
1 hour ago




To be fair, Clinton did win a majority of votes. But they were clustered in such a way that she didn't get enough states. The polls were as accurate as normal, but looking at the country as a whole was misleading.
– Bobson
1 hour ago




3




3




Also, statisticians using aggregations of polls that included correlated polling errors, like FiveThirtyEight, gave Trump something like a 30% chance of winning (I forget the exact numbers) at the time of the election. Statistically, 30% chances occur pretty often...something like 30% of the time I think? It's hard to estimate the correctness of poll-based models to predict elections based on a single event, because having an event with a 30% probability occur doesn't give a ton of evidence against the model. Having the event occur 30 times would, but individual elections happen once.
– Bryan Krause
1 hour ago




Also, statisticians using aggregations of polls that included correlated polling errors, like FiveThirtyEight, gave Trump something like a 30% chance of winning (I forget the exact numbers) at the time of the election. Statistically, 30% chances occur pretty often...something like 30% of the time I think? It's hard to estimate the correctness of poll-based models to predict elections based on a single event, because having an event with a 30% probability occur doesn't give a ton of evidence against the model. Having the event occur 30 times would, but individual elections happen once.
– Bryan Krause
1 hour ago




1




1




Polls directly preceding the election projected a +3.2 advantage for Clinton, who won the actual popular vote by +2.1. That is an error of 1.1 points. The stated margin of error of each individual poll was between 2.3 and 4.5. Taking the average of 10 of these polls would probably produce a lower margin of error, somewhere around 1.5 points. Most individual polls were also within their margins of error, but some were slightly outside (Reuters, NBC, Monmouth, LA Times). The average of all polls was pretty accurate, and this attack on polling is unwarranted.
– John
56 mins ago




Polls directly preceding the election projected a +3.2 advantage for Clinton, who won the actual popular vote by +2.1. That is an error of 1.1 points. The stated margin of error of each individual poll was between 2.3 and 4.5. Taking the average of 10 of these polls would probably produce a lower margin of error, somewhere around 1.5 points. Most individual polls were also within their margins of error, but some were slightly outside (Reuters, NBC, Monmouth, LA Times). The average of all polls was pretty accurate, and this attack on polling is unwarranted.
– John
56 mins ago




2




2




"Polling isn't what it once was", if you think the entire concept of polling has fallen on hard times because a single likely outcome didn't occur, I don't recommend a career in statistics (or gambling).
– Giter
55 mins ago





"Polling isn't what it once was", if you think the entire concept of polling has fallen on hard times because a single likely outcome didn't occur, I don't recommend a career in statistics (or gambling).
– Giter
55 mins ago





1




1




@Ertai87 I think your understanding of the statistics here are incorrect are are not the way that a statistician would describe it. The probabilities are based on the model. Given the model, 30% of the time Result A happens, 70% of the time result B happens. If result B happens, you might use that result to adjust the model in the future, but it gives you limited evidence that the model itself is flawed. Rather, it reflects the fact that the data you used to make predictions in the model were not perfect (and never can be). There is a difference between a wrong model and wrong prediction.
– Bryan Krause
37 mins ago




@Ertai87 I think your understanding of the statistics here are incorrect are are not the way that a statistician would describe it. The probabilities are based on the model. Given the model, 30% of the time Result A happens, 70% of the time result B happens. If result B happens, you might use that result to adjust the model in the future, but it gives you limited evidence that the model itself is flawed. Rather, it reflects the fact that the data you used to make predictions in the model were not perfect (and never can be). There is a difference between a wrong model and wrong prediction.
– Bryan Krause
37 mins ago

















 

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