Course Info: NS-0259
| Course | NS-0259 Intro to Beyesian Modeling |
| Long Title | Introduction to Bayesian Modeling |
| Term | 2025S |
| Note(s) |
Instructor Permission Required Textbook information |
| Meeting Info | Cole Science Center 320 on M,W from 1:00-2:20 |
| Faculty | Kenneth Mulder |
| Capacity | 23 |
| Available | 14 |
| Waitlist | 0 |
| Distribution(s) | |
| Cumulative Skill(s) | |
| Additional Info | Students should expect to spend 6-8 hours weekly on work and preparation outside of class time |
| Description | We live in a world of randomness-not a world of chaos, but a
world in which very few things can be predicted with certainty.
We also live in a world of connections where random events in one
part of a system propagate into other parts of the system and
influence the probability of events there. Bayesian modeling
places a rigorous mathematical framework around the world of
randomness and connections, a framework that can be shaped by
data and used to increase our ability to make predictions and
test hypotheses. In this course, we will learn the fundamentals
of Bayesian models as well as the underlying concepts of
probability and mathematical modeling. Students will apply these
modeling principles to ecological, economic, and social systems.
The course will culminate with students collecting data and
developing and interpreting their own models. Prior experience
in probability and statistics is strongly recommended. Keywords:Statistics, Modeling, Ecology, Probability |