Teaching

EVE 225 - Linear mixed models in ecology & evolution

I really love teaching statistics. I am a firm believer that being a better statistician will help you be a better scientist. Unfortunately, I think lots of students are scared away from statistics early on and don't realize the elegance and simplicity of most statistical methods.

EVE 225 covers the statistical theory nd practical application of general linear models and general linear mixed models using examples drawn from evolutionary and behavioral ecology. It focuses specifically on the analysis of clustered data, e.g. samples taken from the same lake, or measurements made on the same animal, which are common in ecological and evolutionary research. Students will learn 1) the assumptions of traditional linear models and 2) how such hierarchical or nested data violate these assumptions. Students will then learn 3) to build, select and validate mixed models that include random effects and 4) how to interpret and report such results for publication. The lecture portion of the course will focus on building the students’ conceptual framework of the underlying statistics of such models and the discussion/lab section of the course will focus on the hands-on application of each week’s knowledge for analyzing and interpreting example data sets in the statistical computing language R. The course is designed to build on knowledge students would have gained in a basic statistics (e.g. ANOVA, regression) or experimental design course and provide a firm conceptual foundation for students who wish to take more advanced statistical or modeling courses.

A general syllabus for the class and what topics will be covered can be found here.

The course Canvas site can be found here (accessible only if you have a UC Davis login) and recordings of the summer 2020 lectures can be found here (taught as intensive two-week workshop).

EVE 225 is offered every other year in the Winter or Spring quarters (next offering: Winter 2023).

Data Detectives: uncovering mistakes, misconduct and fraud

This first-year undergraduate seminar course explores what happens when we find problems in published scientific work. How do we uncover such problems? What do we do next once we realize that data has been compromised? What are the ethical and legal implications of mistakes and misconduct in scientific research? What practices can we adopt to make mistakes and misconduct less likely to happen and more likely to find? Each week students will read about a case study of data irregularities to understand what happened and the implications of the problems.

Data Detectives will be taught next in Winter 2023

Outreach and broadening participation in science

The Amazon Warrior team is passionate about outreach and broadening participation in science to individuals from groups that have been historically excluded from academic research. In addition to public outreach events, we also participate in several programs designed to share our science with the general public including UC Davis's Ecological and Evolutionary Response to Rapid Environmental Change (EEREC) REU program and the Young Scholars' Program

YSP student Sophia Jin presents results of her summer research project

Kate presents her research at a Soapbox Science event in Berlin