This is the web page for Math 450, taught by Tim Reluga in the spring semester of 2016.

We will learn to model problems and systems using mathematics and computers.
We'll be using the python computer language (which I will
teach everybody at the start of the course). We'll cover statistical models,
cellular automata models, and classical applied-math models. We'll also
discuss the nature of modelling, based on readings from Nate Silver's *Signal
and the Noise*.

Office hours will be Mondays, 1:30 - 2:30, or by appointment.

Computer labs: Jan. 20 and 22, 216 Osmond

Due Wednesday, January 20.

- Read the introduction and chapter 1 of Silver.
- Get and install Canopy on your own computer

Due Friday, January 20.

Due Monday, Feb 1st.

- Read Sections 1 and 2 of Munz et al.'s Zombie theory and this brief review. atleast through model 1.

Due Friday, Feb. 5th.

- In-class presentations

Due Monday, Feb 8th.

- Homework #2
- Read chapters 3, 4, and 5 of Silver, prepare for reading quiz.

Due Wednesday, Feb 17th.

- Partner presentation of a new use of python for us.
- Due Friday, February 5.
- 10-minute in-class presentation.
- Teach use something new and useful about scientific computing with python.
- These turned out very well. I've collected all of the presentations into a single file. When I get your code examples, I'll post those also.

- Lab 1: Introduction to python
- Lab 2: Scientific computing with python

For a formal, structured introduction to computer programming using python, MIT's online course Introduction to Computer Science and Programming is a very helpful reference. Check it out, if you feel like you need more background.

- Introduction
- Geometric curves
- The Black-body theory of global climate - an example model with predictions.
- Lab 1, introduction to python
- Lab 2, Scientific computing with python
- Compartment modelling with differential equations (part 1)
- Compartment modelling with differential equations (part 2)
- Example python code for solving the differential equations from given initial values for the one compartmenta and two compartment models starting from a single dose.

- Predators, Prey, and Reaction rates

Canopy - python software for scientific computing that we'll make use of in class.

The journal Nature has posted some python notebooks that you can experiment with like I will in class.

Google's chrome browser has dropped support for MathML equation rendering, so I suggest using Firefox or Safari.

Kaggle public data science site, with competitions.

Command-line murder, a fun way to learn the unix shell (I think?)

Bokeh is a new library for drawing interactive plots in Canopy.

Google's AI win's at Go (sort-of -- only ranks 600th in the world)

Not even wrong, the book mentioned in class today about some challenges in modern physics. Philosophers, historians, and physcists are still arguing about how to resolve their challenges.

A feud is emerging about the CRISPR synthetic biology technology!

Powerball is in the news, which is reporting on excitement over their billion-dollar jackpot. You can find the odds of winning here. Wired has a slightly wrong take-down of the math. But if you want to win, best to be smart about it -- 1, 2, 3, 4, 5. Also, Planet Money's story on the guy who bought all the tickets to win (which is now illegal), just like in the CLASSIC 80's movie Real Genius.

A new video on the beginnings of molten class sewing. There's more stuff like this in the Gallery of Fluid Motion.

Brooksley Born's story on Frontline about the regulation of deriviative markets, and why some people hold it against Larry Summers.

"Big data" is a dominate idea in technological development right now, closely related to our readings of Nate Silver's book. But there is also a lot of pushback right now. Poster-child of model-free big-data inference Google flu trends seemed to work pretty good at first. Now there's another effort-involving critical analysis of this by Olson, Konty, Paladini, Viboud, and Simonsen as well as cheap commentaries by Butler, Lazer, Kennedy, King, and Vespignani, and Tim Harford helping the limitations of data without models.

Stephen Wolfram's enumeration of 1-dimensional spatial rewrite rules.

Nate Silver was in a fight with Paul Krugman over quantitative journalism. Michael Mann also has some tough comments on Nate's book.