Mathematics predicts probability of immigration reform

The outcome of the Senate vote regarding immigration reform was predicted by Tom Wong with the use of statistical models, according to the Los Angeles Times.  Wong now wants to make use of statistics and mathematics in order to try to influence lawmakers regarding the benefits of reforming the US immigration system, believing that the idea of offering a path to citizenship for undocumented immigrants is unlikely to pass the House of Representatives.

The Los Angeles Times says that Wong had no idea that he did not have citizenship himself until his parents let him know why he was unable to go to a Canadian basketball tournament when he was younger and why he was unable to obtain a driver’s license at the age of 16.  Wong got a green card and was finally able to gain citizenship upon marrying his high school girlfriend back in the March of 2001.  Eventually he was able to start going to classes at University of California Riverside.

Wong was encouraged by these events to come up with a graphic representation that outlines the statistical probabilities of the votes of lawmakers.  The statistics include both solid affirmations and negatives in addition to the odds of any lawmaker changing teams.  There are also some lawmakers who may end up occupying the middle ground and could be viable targets for advocates of immigration reform to encourage them to vote for the bill.

Wong’s analysis suggests that there is little chance of a reform bill that offers a pathway to US citizenship to undocumented immigrants passing the House of Representatives.