- Statistics for Biologists (STT464): This course is a step1 for individuals with no background in statistics. The course covers the basics of the importance of statistical analysis, experimental design, ttests, ANOVAs, chi-squared tests and the like. I found this course particularly helpful when it came to the broad introduction. There is a BRIEF introduction to R/Rstudio. It is setup very much like an undergrad course in statistics would be but is ~90% graduate students.
- Advanced Statistics for Biologists (STT814): This course is largely an introduction to experimental design and SAS. The course runs on the assumption that 464 was completed previously, but doesn’t require many tedious by hand calculations and (in my opinion) serves as a sufficient introduction to many statistical methods and covers more detailed types of tests that may be useful. The caveat is that it is done THROUGH the use of SAS, which is often times frustrating since many have moved to R (rightfully so, in my opinion).
- Computer Science for Evolutionary Biologists (CSE801): Don’t be fooled by the course name! This is a small class that is required for students receiving a particular type of BEACON funding. Evolution is mentioned and appreciated but not the focus of the course in the slightest. It is able to be audited and served as a phenomenal introduction to python and the usefulness of knowing a language. The class is very small and the students sit around and learn python as a group— taught by a computer scientist (often times one that studies artificial intelligence or evolution using digital organisms and the like). The end project requires the development of some sort of model or writing a program that is capable of performing a tedious task (i.e. maze generation and solving or automated sequence alignments). Those who audit the course do not complete the final project and can skedaddle with fresh python skills and no additional gray hairs sprouted as a consequence of completing the final project.
Summary: If you have a background in statistics and are comfortable with ANOVAs and basic tests then the two STT courses will likely not be a fantastic use of your time. If you need a general introduction then STT464 would be useful. If you would like to know more about experimental design and are craving exposure to a statistical software then STT814 is sufficient. The reason I am taking both of these classes is to fulfill satisfactory background to complete IBIO851: Statistical Methods in Ecology and Evolution. This class (I have heard) is supposed to be a thorough course covering use of R and many applied statistical analysis types. The course is mostly filled with eco/evo students who work with LARGE data sets and various experimental types that inevitably require complicated statistics. Colleen (Friesen Lab) took it and has found it helpful even though she does not do experiments of that nature. She would be better to ask and did not complete the first two STT courses. I can offer more input after the fall but it seems like it would potentially be a waste of time for those who do not intend to do an abundance of statistical tests of varying complexity on the regular.