FISH 553 Advanced R programming for natural scientists
Monday and Wednesday 1:30-1:20pm, room MGH 030. Ten combined lecture/labs.
Instructor: Trevor A. Branch, email@example.com office: FISH 322B.
Teaching assistant: Maite Pons, firstname.lastname@example.org, office hours Thursdays 3:00-4:00pm in FSH 329.
Meetings can also be arranged outside these hours with the TA if you are unable to make either set of office hours.
Teaching graduate students how to program in the statistical computing language R.
Course handouts and lectures. No required textbook, but participants would benefit from possessing “The Art of R Programming” by Norman Matloff.
Evaluation and grading
Credit/no credit, 2 credits. Credit awarded based on the completion of all assigned weekly homework exercises, which will average 4-6 hours per week.
Lecture 1. Good programming practices, saving plots, creating functions
Lecture 2. Creating functions, scope, globals
Lecture 3. Loops, if-then-else, while statements
Lecture 4. Writing faster R code, editing existing R functions
Lecture 5. Introduction to maximum likelihood estimation
Lecture 6. Minimizing non-linear functions using mle and optim
Lecture 7. Likelihood profiles and confidence intervals
Lecture 8. Bootstrapping, resampling, simulation-estimation, normal vs. t-distribution
Lecture 9. Debugging in R and Rstudio
Lecture 10. Large projects, pitfalls in R
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