Instructor:
The world is rapidly changing with new information being pushed to us every day. Our society and the problems within it evolve over time. The outdated conclusion may not apply to today anymore and the current findings may not apply in the future. How do we take advantage of the prior knowledge we preserve? How do we understand the new data we observe especially if they are inconsistent with our prior knowledge? When updates are available, how do we combine the new information with our old data? In this course, we will develop our answers to the motivating questions by learning and understanding the idea of Bayesian methodology. We will explore the dynamic procedure of knowledge processing, how prior knowledge can contribute to our understanding, and how biased prior information may lead us to incorrect conclusions. We will use discussions to identify Bayesian data science issues that we are interested in at different stages of the course, use lectures to learn new concepts and tools, and use engaging activities and games in and outside of the classroom to strengthen our understandings.