CSE 357 - Statistical Methods for Data Science

This interdisciplinary course introduces the mathematical concepts required to interpret results and subsequently draw conclusions from data in an applied manner. The course presents different techniques for applied statistical inference and data analysis, including their implementation in Python, such as parameter and distribution estimators, hypothesis testing, Bayesian inference, and likelihood.

3 credits

Prerequisite(s): C or higher in CSE 214 ; AMS 310 ; CSE or DAS major


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