Homework 9 (due Tuesday, December 10, at 11:59pm PST)

1. Tutorials

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

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