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We can try going deeper. I may be making a dumb mistake: when I got to 538 — the main number I see is 89%. I don’t see 89% +- 40. What is his confidence inter

We can try going deeper. I may be making a dumb mistake: when I got to 538 — the main number I see is 89%. I don’t see 89% +- 40. What is his confidence interval?

cyphar 6y ago
If you want a more data-heavy version go to the graphs, then click on the "electoral votes" tab. The shaded part is the 80% confidence interval of each prediction. This is the historical graph form of the "every outcome in our simulations" chart underneath the dot chart. It should be noted that the dot chart at the top of the page does kind of outline the confidence interval (giving a realistic example of what kinds of outcomes might happen) but is obviously geared towards lay-people who don't know what a confidence interval is. > We simulate the election 40,000 times to see who wins most often. The sample of 100 outcomes below gives you a good idea of the range of scenarios our model thinks is possible. I think it would be better if the confidence intervals were better signposted, but it's possible that only the electoral college win margins have solid confidence intervals (I'll admit I don't know enough statistics to know if you could trivially transform the confidence intervals of the electoral college votes to win percentage). The senate and house predictions explicitly show the confidence interval in their main graphs.
- stopachka 6y ago
  I think if you see 90% with 80% confidence interval, you can intuit that he isn't counting uncertainty in the tails. Consider, Would you be comfortable making a bet with someone, on a 90/10 payoff? This, I think is Taleb's central point. Silver's algorithm is not counting the uncertainty correctly.
dragonwriter 6y ago
The 89% probability of victory is the result of the actual predicted electoral vote total and the uncertainty in that prediction. Placing an additional uncertainty on the uncertainty is...very much not understanding uncertainty.
- stopachka 6y ago
  In this case, Taleb's argument stands: 89% implies way too little uncertainty

We can try going deeper. I may be making a dumb mistake: when I got to 538 — the main number I see is 89%. I don’t see 89% +- 40. What is his confidence interval?

cyphar 6y ago

If you want a more data-heavy version go to the graphs, then click on the "electoral votes" tab. The shaded part is the 80% confidence interval of each prediction. This is the historical graph form of the "every outcome in our simulations" chart underneath the dot chart. It should be noted that the dot chart at the top of the page does kind of outline the confidence interval (giving a realistic example of what kinds of outcomes might happen) but is obviously geared towards lay-people who don't know what a confidence interval is. > We simulate the election 40,000 times to see who wins most often. The sample of 100 outcomes below gives you a good idea of the range of scenarios our model thinks is possible. I think it would be better if the confidence intervals were better signposted, but it's possible that only the electoral college win margins have solid confidence intervals (I'll admit I don't know enough statistics to know if you could trivially transform the confidence intervals of the electoral college votes to win percentage). The senate and house predictions explicitly show the confidence interval in their main graphs.

stopachka 6y ago
I think if you see 90% with 80% confidence interval, you can intuit that he isn't counting uncertainty in the tails. Consider, Would you be comfortable making a bet with someone, on a 90/10 payoff? This, I think is Taleb's central point. Silver's algorithm is not counting the uncertainty correctly.

dragonwriter 6y ago

The 89% probability of victory is the result of the actual predicted electoral vote total and the uncertainty in that prediction. Placing an additional uncertainty on the uncertainty is...very much not understanding uncertainty.

stopachka 6y ago
In this case, Taleb's argument stands: 89% implies way too little uncertainty