Learn about the proper role of the government in the economy. The changing role of government and exciting current policy debates motivate the study of this field. We'll introduce a range of topics from externalities to public goods to political economy and then hone in, depending on class interest, one topic such as education or welfare programs.

Sensors are noisy. The world is full of data and events that we want to measure and track, but we cannot rely on sensors to give us perfect information. My kitchen scale gives me different readings if I weigh the same object twice. In simple cases the solution is obvious. If my scale gives slightly different readings I can just take a few readings and average them. Or I can get a more accurate scale. But what happens if the sensor is very noisy, or if data collection is difficult? We may be trying to track the movement of an aircraft or may want to create an autopilot for a self-driving car, both of which require using a lot of information from sensors. This class will be an introduction to how to solve these sorts of filtering problems - where we make sense of the noisy data in a smart way. We'll start with an introduction to probability and then derive the intuition behind how inference works. We'll then derive the basics behind Kalman and Bayesian filters to understand how they blend our noisy and limited knowledge of how a system behaves with the noisy and limited sensor readings to produce the best possible estimate of the state of a system. You'll learn the basics of how planes, self-driving cars, drones, and other systems localize themselves!