This course develops the probabilistic foundations of inference in data science and builds a comprehensive view of modeling and decision-making. Emphasis is on the nature of randomness, the power and limitations of inference, and the consequences of decision making. Students will experience probability, statistical inference, and the modeling of processes through the lens of simulation using the statistical programming language R. Prerequisites: Any one of DATA_SCI 1030 or STAT 1200 or STAT 2500 or instructor’s consent.