Wed, Nov 20, 2013 -- Running evolutionary models in replicate, calculating and plotting 95% confidence intervals
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We will have class next week, Nov. 27th
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For those who missed class last week, we *will* be having class next week, Nov. 27th.

Next week will be a hands-on workshop covering some useful Python scientific computing libraries. Be sure to bring your laptop.

Homework 7 solutions
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We will go over the solution to the `evolutionary digital modeling homework <http://nbviewer.ipython.org/urls/raw.github.com/beacon-center/2013-intro-computational-science/master/notebooks/hw7-Animal%20Foraging%20and%20the%20Evolution%20of%20Goal-Directed%20Cognition.ipynb>`__.

This homework was tough, so we will dedicate plenty of class time to walk through it. Come to class with specific questions about the issues you ran in to.

Here is the notebook that we covered in class showing you how to plot the average and SEM for multiple files: http://nbviewer.ipython.org/7572328

Homework 8 - Final project
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We will be expanding the model from the `evolutionary digital modeling homework <http://nbviewer.ipython.org/urls/raw.github.com/beacon-center/2013-intro-computational-science/master/notebooks/hw7-Animal%20Foraging%20and%20the%20Evolution%20of%20Goal-Directed%20Cognition.ipynb>`__ for a final project. This project will cover the next two weeks. You may work on this project in groups of up to 4 people, but you can do a solo project if you prefer.

For the first week, you will decide as a group on an interesting (and feasible^) extension of the model and begin implementing it and gathering data from the model. For the second week, you will analyze the data, plot the data, and write up a 2-page report.

Email the homework solutions to Randy Olson: olsonran AT msu DOT edu


^ Please contact me if you're unsure about the extension you want to pursue.