Philosophical Foundations of Statistics

Statistics is fundamentally about using data to make informed decisions about the unknown, whether it is the effect of a new drug or the results of an upcoming election. While statisticians agree that data is inherently random, they disagree about the unknown factors we seek to understand. Are these factors themselves random, or are they fixed but unobservable? This question has sparked bitter debates, dividing statisticians into two camps: Bayesians, who view these unknowns as random, and frequentists, who treat them as fixed. This seminar will introduce students to both perspectives, examining how each approach affects the theory and practice of data analysis and engaging students in this age-old debate. This seminar covers the equivalent content of Stats 200 and is accepted by the Data Science major, Data Science minor, and Statistics minor as a substitute for Stats 200. Enrollment limited to undergraduates, with preference to sophomores. Prerequisite: A course in probability theory.