This page will be updated as the semester goes on, if you want to use this RSS feed to track them. Alternately, lecture notes will be linked to on the course syllabus, which includes the readings.

- Lecture 25 (April 22): Inference on networks
- slides
- Lecture 24 (April 15): Contagion on networks
- slides
- Lecture 23 (April 10): Collective phenomena and self-organization in agent-based models
- slides
- Lecture 22 (April 8): Agents and Agent-Based Models
- slides
- Lecture 21 (April 3): Complex networks 2
- slides
- Lecture 20 (April 1): Complex networks 1
- slides
- Lecture 19 (March 25): Inference from simulations
- slides; R
- Lecture 18 (March 20): Special problem-solving session for homework 2
- partial solutions; R
- Lecture 17 (March 18): Error Statistics and Severe Testing
- slides
- Lecture 16 (March 6): Heavy tails 4, testing and evaluation
- slides and R
- Lecture 15 (March 4): Heavy tails 3, estimation
- slides
- Lecture 14 (February 28): Heavy tails 2, origins
- slides
- Lecture 13 (February 26): Heavy tails 1, basics
- General R files for the next several lectures
- slides; R
- Lecture 12 (February 21): Self-organization 2
- slides
- Lecture 11 (February 19): Cellular automata 2/Excitable media
- slides
- Lecture 10 (February 14): Cellular automata 1
- slides
- Lecture 9 (February 12): Self-organization 1
- Philip and Phylis Morrison and the Office of Charles and Ray Eames, Powers of Ten
- slides
*see also:*Pattern Formation in Cocktails- Lecture 8 (February 7): Determinism and randomness
- Henri Poincaré, "Chance" (from Science and Method, 1908)
- slides
- Lecture 7 (February 5): Information theory
- slides
- M.C. Hawking, "Entropy", from Fear of a Black Hole [lyrics; mp3 (radio-safe Brief History of Rhyme version)]
- Ray and Charles Eames, A Communications Primer
- Lecture 6 (January 31): Inference for Markov chains and related processes
- slides
- Note: Maximum Likelihood Estimation for Markov Chains
- Lecture 5 (January 29): Symbolic dynamics; stochastics from dynamics
- slides
- Note: More on the Topological Entropy Rate
- Lecture 4 (January 24): Attractor reconstruction and nonlinear prediction
- slides (see slides for R examples).
- Note: Nonlinear prediction, nearest-neighbors, kernel methods
- Lorenz time-series generator, written in Perl.
- the Lorenz time series used in the lecture
- Lecture 3 (January 22): Attractors
- slides; R
- Lecture 2 (January 17): More chaos
- slides; R
- The Arnold Cat Map Movie (starring Marlowe the Cat, directed by Evelyn Sander)
- Lecture 1 (January 15): What is a dynamical system? What is chaos? What is a simulation?
- slides; R

Corrupting the Young; Complexity; Enigmas of Chance; Networks

Posted at April 22, 2008 16:03 | permanent link