Bayes likes Obama
As I have noted previously, one can use Bayes theorem to evaluate the conditional election prospects of various Presidential candidates for 2008.
Here is the logic. Let A be the event that a candidate wins the general election, and B be the event that a candidate wins his or her party's nomination. Tradesports gives us the betting market's view of P(A) and P(B). It is a safe assumption that P(B / A) = 1, that is, a candidate can win only if nominated. We can then use Bayes theorem to compute P(A / B), the probability that the candidate will win the general election conditional on being nominated.
Based on the most recent transaction prices, here is what you learn about the conditional probabilities:
Obama 88 percent
Gore 80 percent
Giuliani 65 percent
McCain 63 percent
Clinton 51 percent
Romney 50 percent
Edwards 44 percent
The market suggests that Obama would be the strongest candidate if nominated.
By the way, Steve Levitt likes Obama, too.
Here is the logic. Let A be the event that a candidate wins the general election, and B be the event that a candidate wins his or her party's nomination. Tradesports gives us the betting market's view of P(A) and P(B). It is a safe assumption that P(B / A) = 1, that is, a candidate can win only if nominated. We can then use Bayes theorem to compute P(A / B), the probability that the candidate will win the general election conditional on being nominated.
Based on the most recent transaction prices, here is what you learn about the conditional probabilities:
Obama 88 percent
Gore 80 percent
Giuliani 65 percent
McCain 63 percent
Clinton 51 percent
Romney 50 percent
Edwards 44 percent
The market suggests that Obama would be the strongest candidate if nominated.
By the way, Steve Levitt likes Obama, too.
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