tag:blogger.com,1999:blog-6383772914939427705.post7971191515316871589..comments2023-10-30T02:33:51.535-08:00Comments on Alaska Political Corruption: Why Were So Many Experts Surprised by Obama's Victory?--UPDATEDCliff Grohhttp://www.blogger.com/profile/13494299086745035172noreply@blogger.comBlogger2125tag:blogger.com,1999:blog-6383772914939427705.post-46312509315799487342012-11-17T18:17:14.407-09:002012-11-17T18:17:14.407-09:00I agree with Karl.
You review the positive reason...I agree with Karl.<br /><br />You review the positive reasons the pundits had for holding their (as it turned out, false) opinions. That makes them sound reasonable.<br /><br />You did not address the weighing of reasons. What weight should a rational person assign to the various reasons for a particular outcome? In particular, what weight should someone assign to the polling evidence, especially the cumulative evidence of all the polls? <br /><br />For the most part, a rational person will assign a large amount of weight to this kind of evidence and a very small amount of weight to the other sorts of reasons. Polling analysis has improved since "Dewey defeats Truman." It is now quite reliable (not a single poll but all of them aggregated and analyzed by a careful statistician). So are the presidential election markets.<br /><br />Consider this analogy. Will my friend, John Smith, drink coffee on Monday morning? You might speculate. He needs caffeine to energize him at work. His parents and everyone in his family drink coffee. He likes coffee ice cream. All plausible reasons to think he will drink coffee on Monday. However, what if someone observed John every morning for the past two weeks. That person reports to you that John never drank coffee in the morning. All your other reasons go out the window. (More accurately, your belief is updated base on new evidence and the new evidence swamps the old evidence). The old reasons are a factor, but not a large one. You should predict that John will not drink coffee on Monday. <br /><br />The pundits were not listening to the reported observations. They held onto their prior reasons and gave them too much weight. Their Bayesian updating was very poorly conducted, if at all (they are probably not Bayesians anyway, which is too bad).Cliff Landesmanhttps://www.blogger.com/profile/09060433336423891959noreply@blogger.comtag:blogger.com,1999:blog-6383772914939427705.post-31183863594649664572012-11-11T13:10:10.134-09:002012-11-11T13:10:10.134-09:00Even if some polls were biased, the poll averages ...Even if some polls were biased, the poll averages both nationally and in the swing states both favored Obama and showed significant momentum toward him in the last few days of the campaign. To miss all of that is beyond living in a bubble; it's willful blindness.Anonymoushttps://www.blogger.com/profile/07790182901540367722noreply@blogger.com