From https://xkcd.com/892/
BIOL 301, Biostatistics
Biostatistics, taught alternate spring semesters, provides a general introduction to statistics for biology majors, with an emphasis on data analysis and understanding statistical distributions. Students learn how and why to conduct basic statistical analyses such as t-tests, linear regressions, and ANOVA, while developing an understanding of the general principles of statistics. In this class we will go through the whole process of using biological data to answer a scientific question, from extracting basic summary statistics, to visualizing data, conducting a analysis using inferential statistics, and interpreting that analysis.
This 4-unit class is set up as two lectures and a four-hour lab weekly, which include a combination of mini-lectures, problem solving sessions, and hands-on activities. Exercises are conducted in the statistical software R. Problem sets provide practice of the techniques and help students develop a deeper understanding of the concepts. Throughout the course of the semester, students also work on an independent project conducting an analysis of data from a published data set or their own research. Students who are conducting research in the biology department in preparation for their capstone will find this course particularly valuable for their own work. This course is also recommended as a prerequisite for my Ecology and Evolution of Disease course.
Data Camp graciously provides us with free education access to online tutorials in R as part of this course.
BIOL 494, Ecology and Evolution of Infectious Disease
This upper division course focuses on fundamental topics in the ecology and evolution of infectious disease, including epidemiological SIR-type models, the basic reproductive ratio R0, the evolution of virulence, vaccination and herd immunity, and antibiotic resistance. Students read primary literature, interpret visual representations of data, and practice scientific writing. Students also learn basic SIR modeling using the statistical software R, and conduct an independent project modeling an infectious disease over the course of the semester. This course is great preparation for conducting disease ecology research with me as an independent research student. Ecology (BIOL-300) is required as a pre-requisite, and Biostatistics (BIOL-301) is strongly recommended.
