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