Using data to inform public policy decision is a challenge given the multiple, and sometimes competing, goals for public agencies. Public transit agencies often have large amounts of data, but the data are not always accurate, and there are problems to solve where no data exists. Informing policy outcomes requires identifying the right problem, following the data to find the right research questions, accepting some level of uncertainty, and determining the right way to visualize the results based on the audience. This paper assumes a limited understanding of statistics and basic knowledge about public transit systems.