STAT 391

Quantitative Introductory Statistics for Data Science
4.0 credits

Course Description

The basic concepts of statistics, machine learning and data science, as well as their computational aspects. Statistical models, likelihood, maximum likelihood and Bayesian estimation, regression, classification, clustering, principal component analysis, model validation, statistical testing. Practical implementation and visualization in data analysis. Assumes knowledge of basic probability, mathematical maturity, and ability to program. Prerequisite: either CSE 312, or STAT 394/MATH 394 and STAT 395/MATH 395. Offered: Sp.

Upcoming Time Schedule

Spring, 2023

SLN/Section Time Location Instructor
20160 A
Open

T Th 12:30PM - 2:20PM

ECE 125

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