Students also identify ways to perform data analysis by making use of statistical tests and various forms of visualization. At the end of the semester, students communicate their results in a Python Jupyter Notebook with annotated analysis and through a research presentation. In this course-embedded research (CER) course, student spend the first half of the semester learning the basics of astrophysics by using Python Jupyter notebooks that incorporate real astrophysical data. Students spend the second half of the semester carrying out research projects. These projects require to students to think critically about the data required to answer research question, and to obtain the data using SQL searches with the online Sloan Digital Sky Survey database. Achieves technology student learning outcomes a, b, c, and d.

View PHY 3130 in the Academic Catalog

Approved for Data Intensive Course Designation starting Spring 2024.