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PHYSICS89L

Introduction to Data Analysis, with Python and Jupyter

Physics H&S - Humanities & Sciences

Course Description

How do we draw conclusions about fundamental physics from experimental data? This course covers basic data analysis techniques and practical statistics used in experimental and computational physics research. Weekly Python-based labs will allow students to explore topics including data visualization, error propagation, evaluating hypotheses, and fitting analytical models. These labs incorporate real and simulated data from existing experiments such as a gamma-ray telescope and a detector that searches for dark matter. Students will learn to use Python libraries running in Jupyter Notebooks to analyze data and will, for example, study the rate at which the universe is expanding using existing data from multiple telescopes. No prior coding experience is required.Corequisite: Physics 71

Grading Basis

RSN - Satisfactory/No Credit

Min

1

Max

1

Course Repeatable for Degree Credit?

No

Course Component

Lab Section

Enrollment Optional?

No

Course Component

Lecture

Enrollment Optional?

No

Does this course satisfy the University Language Requirement?

No

Courses

PHYSICS89L is a prerequisite for:

Programs

PHYSICS89L is a completion requirement for: