This advanced topic course delves into five critical ideas and insights that have significantly impacted the fields of statistics and data science. From foundational concepts to influential advancements, each topic is selected for its historical significance and enduring impact. Students will develop a deep appreciation for these key ideas, associated insights, and their role in shaping contemporary statistical theory and practice. For each topic, we will discuss motivations, innovations, and impacts through presentations and discussions. Students will be required to read important papers and share their perspectives. Although many topics fit this criterion, the list includes, but is not limited to, influence functions, resampling, adaptive designs, dimension reduction, data augmentation, regularization, identifiability, and propensity scores. Depending partly on the interests of the students, we will select and focus on five topics over the course of one semester. Prerequisites: SDS 5020 and 5071.
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