Homework 9 (due Tuesday, December 10, at 11:59pm PST)
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1. Tutorials
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I've prepared several tutorial videos for this homework.

Working with the evolutionary digital model: http://www.youtube.com/watch?v=kXKJQHaFWnU

Saving data to a file in Python: http://www.youtube.com/watch?v=irnj19jz8uI

Computing and plotting estimated 95% confidence intervals in Python: http://www.youtube.com/watch?v=4N5Uo3XOTNQ

There are also several useful tutorials below.

pandas & SciPy tutorial: http://www.randalolson.com/2012/08/06/statistical-analysis-made-easy-in-python/

pandas video tutorial: http://vimeo.com/59324550

matplotlib tutorial: http://matplotlib.org/users/pyplot_tutorial.html

2. Final project report
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This week, you will prepare a 2-page final report on your findings from homework 8. Prepare it as a scientific report:

* introduction to the problem and what you're studying

* motivate why it's interesting

* discuss related work (optional, but may strengthen your case for why it's interesting)

* explain your methods for exploring the problem

* show the data that you measured from your experiments

* use statistics and your data to show what you discovered

* discuss the possible implications of the findings

* discuss the limitations of the findings

* suggest possible followup projects

Deliverables should include:

* Final project report in PDF format

* Code for the extended model

* Raw data and code used for all data analysis and plotting (as a nbviewer link)

**Make sure to include the names of everyone in your group in the final project report.** Email the homework solutions to Randy Olson: olsonran AT msu DOT edu