- Category
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Course Syllabus
- Name
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Chaos, Complexity, and Inference
- Image
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- Description
- This course will cover some key parts of modern theories of nonlinear dynamics ("chaos") and complex systems, and their connections to fundamental aspects of probability and statistics. By studying systems with many strongly-interacting components, students will learn how stochastic models can illuminate phenomena beyond the usual linear/Gaussian/independent realm, as well as gain a deeper understanding of why stochastic models work at all.
- Institution
- Carnegie-Mellon University
- Author
- Cosma Shalizi
- Topics
- Nonlinear Dynamics, Chaos, Complex Systems, Statistics, Information Theory, Modeling
- URL
- http://www.stat.cmu.edu/~cshalizi/462/
