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PHY 5362: Computational Insight

Spring 2027 · 3 credit hours · 1 section · 20 open seats as of Oct 30, 2026, 2:04 AM Central

Prerequisite(s): Recommended: CSI 1430 or PHY 2360, PHY 3175 and PHY 3176, or by permission of instructor. This is a practicum in computer programming, statistical methods and data analysis. The goal of the class is to provide students with the general tools needed for data analysis in experimental physics, computational analysis observational astrophysics, and related research topics. Students will learn to use Python and R for data analysis; use best practices in data visualization; understand what questions are addressed by correlation tests, hypothesis tests, and model fitting; define and perform model fitting in both a frequentest and Bayesian framework; understand various Monte Carlo sampling techniques, data simulation methods, and model validation; provide statistical error estimation; selecting between models; and other related topics.

Professors teaching PHY 5362 in Spring 2027

Ben Rose. See their BUBooks scores and reported grades in the builder.

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