DSCI 3212 - Probability and Mathematical Statistics for Data Science

Prerequisite: DSCI 2109. Prerequisite: DSCI 2109. This is a foundational course for data science. In this connector course we will state precisely and prove results discovered while exploring data in DSCI 2109. Topics include: probability, conditioning, and independence; random variables; distributions and joint distributions; expectation, variance, tail bounds; Central Limit Theorem; symmetries in random permutations; prior and posterior distributions; probabilistic models; bias-variance tradeoff; testing hypotheses; correlation and the regression model. 3 credits.