This course teaches data analysis, but it focuses on scientific models first. The unfortunate truth about data is that nothing much can be done with it, until we say what caused it. We will prioritize conceptual, causal models and precise questions about those models. We will use Bayesian data analysis to connect scientific models to evidence. And we will learn powerful computational tools for coping with high-dimension, imperfect data of the kind that biologists and social scientists face.
Evolving an Open, Networked, and Interdisciplinary Evolution & Sustainability Education Research Community
We are scientists, artists, teachers, and students working together to reimagine and cultivate a new direction for evolution and sustainability education. We believe interdisciplinary perspectives in evolutionary anthropology can serve as a foundation for understanding and valuing the science of evolutionary change in our everyday lives and global society. Join us!
In this blog series on teaching Open Science in the field of linguistics, Naomi Truan and Dennis Dressel reflect on their leanings process and challenges and joys when they decided to publish their teaching material as Open Education Resources and to foster Open Science in their seminar.
As a linguist (pronouns: she/her), I am interested in topics at the intersection of language and society such as Twitter interactions, students’ language ideologies towards their own digital language use, multiethnolects in urban spaces, or person reference (that is, how do we talk to and about people?). I am also committed to Open Science and science communication, and blog regularly on academic writing and emotions and vulnerability in research and teaching. I also enjoy leading workshops on these topics.