No matter our focus, data and information are relied upon in making decisions, building hypotheses, or in trying to show the connection of one idea or thought to another. In order to better understand (or argue against) a claim, we need to make sure we understand what the data is telling us and how it can be interpreted.
This course will build towards understanding the basic statistical methods: hypothesis testing, confidence intervals, linear regression, chi squared tests and tests of statistical significance. It will work to explain the results of those tests, and how to interpret them in context.
This is an introductory statistical course, designed for any student interested in learning the basics of statistical tests and how to use them. No prerequisites are required.
Learning Outcomes:
Delivery Method: Hybrid in-person and remote, with faculty in-person
Prerequisites:None.
Course Level: 2000-level
Credits: 2
Synchronously TBA (1st seven weeks)
Maximum Enrollment: 20
Course Frequency: One time only
Categories: All courses , Mathematics
Tags: environmental science , Public Action , public policy , quantitative reasoning , science , social science