Biol697 An introduction to Computational Data Analysis in Biology

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R

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R

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This course will cover the basic statistical knowledge necessary for a graduate student to design, execute, and analyze a basic research project. The course aims to have students focus on thinking about the biological processes that they are studying in their research and how to translate them into statistical models. The course will take a hands-on computational approach, teaching students the statistical programming language R. In addition to teaching the fundamentals of data analysis, we will emphasize several key concepts of efficient computer programming that students can use in a variety of other areas outside of data analysis.

I will assume a basic knowledge of algebra and introductory calculus (although no calculus will be used). Undergraduate courses in probability theory and computer science are useful, but not required. Students who are new to programming should skim chapter 1 of Adler before beginning the course.

Also, you must install R and R-studio on your laptop before the first day of class. Please bring your latop to all classes.

Adler, J. (2009) R in a Nutshell: A Desktop Quick Reference. O'Reilly. [amazon]

Media. Vickers, A. (2009) What is a p-value anyway? 34 Stories to Help You Actually Understand Statistics. Addison Wesley. [amazon]

Whitlock, W.C. and Schluter, D. (2008) The Analysis of Biological Data. Roberts and Company Publishers. [amazon]

I will be drawing on examples and materials from a few other sources. They include wonderful examples of R code in the context of data analysis. You are not required to have these, but you will either find them useful in this course or in future endeavors.

Bolker, B. (2009) Ecological Models and Data in R. Princeton University Press. [link with preprint]

Matloff, N. (2011) The Art of R Programming: A Tour of Statistical Software Design. No Starch Press. [no startch]

Song, S. Qian (2009) Environmental and Ecological Statistics with R. Chapman and Hall/CRC Press, London. [amazon]

Your grade will be determined by a combination of weekly homework, a midterm, and a final exam. Homework will consist of a problem set and a short response to a chapter from Vickers. Homework will be worth 50% of your course grade. All exams will be take-home. The midterm will be worth 20% and the final will be worth 30%. Additionally, students may earn extra credit for a statistical write-up of their own research data to be turned in during the finals period.

All homework is open book, open internet (save looking for answer keys). Feel free to discuss the work with your classmates, but your answers must be your own. Exams will be open book, open internet, but no collaboration between classmates.

Every week we will have assigned readings from the above texts and other papers and chapters at my discretions. PDFs will be provided as needed. Assignments for that week will be due the following Tuesday.