STAT5731: Bayesian Astrostatistics

4 Credits

This course will introduce Bayesian methods for interpreting and analyzing large data sets from astrophysical experiments. These methods will be demonstrated using astrophysics real-world data sets and a focus on modern statistical software, such as R and python. prereq: MATH 2263 and MATH 2243, or equivalent; or instructor consent Suggested: statistical course at the level of AST 4031, AST 5031, STAT 3021, or STAT 5021

View on University Catalog

All Instructors

B+ Average (3.182)Most Common: A (42%)

This total also includes data from semesters with unknown instructors.

12 students
WFDCBA
  • 5.17

    /6

    Recommend
  • 5.22

    /6

    Effort
  • 5.43

    /6

    Understanding
  • 5.13

    /6

    Interesting
  • 5.46

    /6

    Activities


      Contribute on our Github

      Gopher Grades is maintained by Social Coding with data from Summer 2017 to Summer 2025 provided by the University in response to a public records request

      Not affiliated with the University of Minnesota

      Privacy Policy