In the first chapter of his book Data Analysis for Politics and Policy, Yale researcher Edward R. Tufte demonstrates the opportunities as well as the challenges of using data to help inform decisions of public policy. First, Tufte sets forth the various terms and theoretical frameworks he will be using to analyze data. He advocates the use of what he calls a “multivariate analysis” which takes into account several describing variables to understand a problem rather than just one. In scientific settings, it is possible to isolate a single describing (independent) variable from others and provide a control by which to reach a conclusion regarding the cause of a given response (dependent) variable. But in the real world of social problems and political policy, it is often impossible to parse out the effects of the multitude of possible describing variables that may be at play in a given situation. For Tufte, that gives rise to the need for a “statistical technique” that “may help organize or arrange the data so that the numbers speak more clearly to the question of causality.” The numbers cannot answer the question of causality, but they can help shed light on it if they are analyzed in such a way that takes into account as many different variables as possible.