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STAT 4321

Inferential Data Science Foundations II

0.5 credit · Undergraduate

Inferential data science tools extending to big data using open-source software. Asymptotic properties of likelihoods, parametric and non-parametric approaches, bootstrap, jackknife estimation, frequentist and Bayesian perspectives. Formal tools are developed. Concepts are demonstrated using simulation. Abstract concepts are made concrete through visualization and numerical computation.

Prerequisites & course information

Precludes additional credit for STAT 3509 or STAT 3559 . Prerequisite(s): STAT 2210 . Lectures three hours a week, laboratory one hour a week.

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