DATA375

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DATA375 - Introduction to Statistical Computing

Mathematics Undergraduate UA - UA General

Course Description

Basic computing skills including random variable generation, Monte Carlo integration, visualization, optimization techniques, re-sampling methods, Bayesian approaches, and introduction to statistical computing environments (R and Python). Material will provide hands-on experience with real world problems. It is expected that students have prior experience in a programming language, preferably Python.

Min Units

3

Max Units

3

Repeatable for Credit

No

Grading Basis

GRD - Regular Grades A, B, C, D, E

Career

Undergraduate

Enrollment Requirements

017805

Name

Lecture

Workload Hours

3

Optional Component

No

Typically Offered Main Campus

Fall, Spring

Typically Offered Distance Campus

Fall

Typically Offered UA Online Campus

Not Offered

Typically Offered Phoenix Campus

Not Offered

Typically Offered South Campus

Not Offered

Typically Offered Community Campus

Not Offered