Saill White has been working to make complex data easy to understand for the past three decades. With a degree in Physics from UC Berkeley, her first job after college was helping scientists at Lawrence Berkeley National Laboratory make sense of stellar search and supernova data. She has since worked in the fields of building energy efficiency, artificial intelligence, operating system virtualization and web interface development. In April 2017 she became aware of a very odd and pervasive statistical implausibility with respect to election data. Statisticians were reporting that in many counties in certain states there were a higher percentage of votes for the Republican candidate in precincts where more ballots were cast. Believing that this implausible correlation must be due to cherry-picked counties with unevenly distributed demographics, she applied her programming and data visualization skills to the task of performing this analysis for ALL the counties and precincts participating in a given race.