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: DSCI 301 . Recommended Prerequisite(s): MATH 212 . Mutually Exclusive: Cannot register for STAT 315 if student has credit for ECON 307 / STAT 310→STAT 315→unlocks 61 courses

61 mapped courses list STAT 315 as a prerequisite. See on the map →

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