The syllabus for this course can be found here.
The final write-ups for final group projects are due Monday, December 1st, 2014. On Dec 2nd and 3rd students will meet with Prof Towers to receive feedback on their project and writeup.
Each of the project groups will perform an in-class 20 min presentation on Monday, Dec 8th, 2014 and Wed, Dec 10th, 2014. By Dec 9th, all group members are to submit to Prof Towers a confidential email, detailing their contribution to the group project, and detailing the contributions of the other group members.
The list of modules for the Fall 2014 course in computational and statistical methods for mathematical biologists and epidemiologists:
- Literature searches with Google Scholar
- Extracting data from graphs in published literature
- Online sources of free data
- Homework #1, Due Sep 2nd 2014 at noon.
- Module I: The basics of the R statistical progamming language
- Homework #2, Due Sep 10th 2014 at noon.
- as part of the homework, read the modules “How to write a good scientific paper”, and “How to download an R script from the internet and run it”.
- Module II: Epidemic modelling with compartmental models
- Homework #3, Due Sep 17th 2014 at noon.
- Module III: SIR disease model with age classes
- Homework#4, Due Sep 24th 2014 at noon.
- Module IV: SIR modelling of influenza with a periodic transmission rate
- Module V: fitting the parameters of an SIR model to influenza data using Least Squares and the Monte Carlo parameter sweep method
- Module VI: an overview of goodness of fit statistics, and methods to fit parameters of mathematical models to data
- Module VII: estimating parameter confidence intervals when using the Monte Carlo parameter sweep optimization method
- Homework#5, Due Wed Oct 8th 2014 at noon.
- Module VIII: Basic Unix
- Module IX: introduction to C++ for computational epidemiologists
- Homework #6, Due Mon Oct 20th 2014 at noon.
- Module X: a C++ class to solve ordinary differential equations
- Homework #7, Due Mon Nov 3rd 2014 at noon. (assignment emailed)
- Getting started using the NSF XSEDE distributed computing system
- An example of submitting a batch job to XSEDE Stampede
- Module XI: another example C++ program, fitting SIR model parameters to CDC Midwest 2007-08 B influenza data
- Homework #8, Due Mon Nov 10th 2014 at noon.
- Submitting jobs to the ASU A2C2 ASURE batch computing system
- Correcting the Pearson chi-squared statistic for over-dispersed data
- Homework #9, Due Wed Nov 19th 2014 at noon.
- Module XII: another example of the parameter sampling model optimization method: using Negative Binomial likelihood
- Module XIII: practical problems when connecting deterministic models to data
- Module XIV: submitting jobs in batch to the ASU Saguaro distributed-computing system
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