Special Topics: Computational Statistical Methods in Life Sciences

9 units · Undergraduate

Intermittent: 9 units The life sciences are rapidly becoming data-driven fields due to technological advancements in genomics, neuroscience, epidemiology, and other areas. Statistical methods are essential for analyzing complex datasets that arise in these disciplines, such as genomic sequences, neuroimaging data, and public health records. This course will introduce statistical techniques for analyzing data-driven life science problems, emphasizing computational aspects from a Bayesian perspective. Prerequisite: 36-401 Min. grade C