tag:blogger.com,1999:blog-6695411995525437118.post2883101180966921795..comments2020-11-08T18:58:22.197-07:00Comments on Big Sky Political Analysis: Voter Fraud in Montana's Senate race? Not so much.David Parkerhttp://www.blogger.com/profile/16269564495760820631noreply@blogger.comBlogger3125tag:blogger.com,1999:blog-6695411995525437118.post-28888057521644420942012-11-21T10:10:37.933-07:002012-11-21T10:10:37.933-07:00The guy that authored that study is a retired NSA ...The guy that authored that study is a retired NSA scientist.Ryan Bradynoreply@blogger.comtag:blogger.com,1999:blog-6695411995525437118.post-74108373426306811782012-11-21T08:09:02.046-07:002012-11-21T08:09:02.046-07:00Ryan--
Excellent post. Yes, the 2BL test would be...Ryan--<br /><br />Excellent post. Yes, the 2BL test would be unable to detect all fraud (particularly fraud linked to computer software). Even a positive test does not prove fraud--only that fraud may exist. The results I report do suggest that that type of fraud Ms. Hall was suggesting, however, is likely not present. Just for kicks, I ran the analysis separately on precincts won by the Democrats and precincts won by the Republicans. Again, the results did not detect any statistically significant deviance from the expected distribution of significant digits.<br /><br />ParkerDavid Parkerhttps://www.blogger.com/profile/16269564495760820631noreply@blogger.comtag:blogger.com,1999:blog-6695411995525437118.post-18043423609314319742012-11-20T23:46:48.794-07:002012-11-20T23:46:48.794-07:00Unfortunately, this analysis does not support your...Unfortunately, this analysis does not support your conclusion that vote fraud played no role. <br /><br />Benford's Law can only detect irregularities in digit distribution for data sets with certain qualities. Those data sets must be governed by at least one rule in which numbers are assigned. For example, in a list of prices for goods sold, Benford's Law would detect the irregularity of the recurring "9" at then end of most prices. Take humans assigning numbers as another example: people subconsciously repeat certain digits, which undermines randomness and allows Benford's Law to detect tendencies.<br /><br />Benford's Law <b>cannot</b>, however, detect irregularities in data sets comprised of numbers produced from mathematical combinations--because there are no irregularities. <br /><br />Your statistical analysis shows no irregularities in the last digit of the precinct totals. But this implies that someone would have been picking numbers for precinct totals. In that case, yes, your method would detect the irregularities due to humans' inability to model randomness when picking numbers.<br /><br />But not all vote fraud has to be the product of the human mind. To limit your analysis only to this, and then to conclude no vote fraud took place, is simply illogical. Take, for example, a formula where n = reported precinct vote total for candidate x, and r = the actual precinct vote total for candidate x. Now let's say n = r + 1. In this formula, candidate x's vote total would be fraudulently increased by 1 at every precinct. If every final digit is skewed up by 1, Benford's Law will have absolutely nothing to say on whether the actual precinct vote total was altered, because it will still detect the same variation of digits in the last placeholder. <br /><br />More realistically, a computerized vote fraud model might flip every 20th vote for candidate x to candidate y. If that's the case, the data set will still be comprised of numbers produced purely from mathematical combination, and no irregularities will be detectable. <br /><br />You have only proven a human did not pick numbers out of the air. You have not proven vote fraud didn't happen. Granted, I'd like to think Ms. Hall is mistaken, anyway(!), but there's nothing in your analysis to affirmatively show this.Ryan Bradynoreply@blogger.com