Probability and Statistics for Data Science

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MATH 102 or MATH 106 Description: An introduction to mathematical statistics and computation for applications to data science. Topics include probability, random variables expectation, sampling distributions, estimation, confidence intervals, hypothesis testing and regression. A weekly lab will cover the statistical package, R, and data projects. Cross-list: STAT 315 . Recommended Prerequisite(s): MATH 212 . Mutually Exclusive: Cannot register for DSCI 301 if student has credit for ECON 307 / STAT 310→DSCI 301→unlocks 52 courses

52 mapped courses list DSCI 301 as a prerequisite. See on the map →

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