DATA 330 Statistical Methods for Data Science

A course in the statistical tools commonly used in data science applications. Understanding the assumptions and interpreting the results for valid data-driven decision-making will be emphasized. Topics include A/B testing, ANOVA, and multiple linear regressions. Pre-requisite(s): DATA 220; MATH 126 and MATH 127 OR MATH 181

Lecture/ Lab Credits: 3+0

Credits

3.00