Statistical Methods for Linguistics and Psychology 2020
The course was taught virtually, using pre-recorded videos, moodle, and Zoom for daily real-time meetings.
About SMLP
The summer school aims to fill a gap in statistics education, specifically within the fields of linguistics and psychology.
One goal of the summer school is to provide comprehensive training in the theory and application of statistics, with a special focus on the linear mixed model.
Another major goal is to make Bayesian data analysis a standard part of the toolkit for the linguistics and psychology researcher.
Over time, the summer school has evolved to have at least four parallel streams: beginning and advanced courses in frequentist and Bayesian statistics. These may be expanded to more parallel sessions in future editions.
Funding
This summer school is funded by the DFG and is part of the SFB 1287, “Limits of Variability in Language”.
Dates
7-11 September 2020
Location
Online
Language
English
Target group
students and professionals
Fee
no fee
Curriculum
- Introduction to Bayesian regression modeling with rstanarm (maximum 30 participants). Taught by Jonah Gabry, assistant: Shravan Vasishth
- Advanced Bayesian data analysis (maximum 30 participants). Taught by Bruno Nicenboim and Shravan Vasishth
- Foundational methods in frequentist statistics (maximum 30 participants). Taught by Audrey Buerki, Daniel Schad, and João Veríssimo
- Advanced methods in frequentist statistics with Julia (maximum 30 participants). Taught by Phillip Alday, Douglas Bates, and Reinhold Kliegl
Invited lecturers
- Douglas Bates (co-instructor for Advanced methods in frequentist statistics with Julia)
- Phillip Alday (Advanced methods in frequentist statistics with Julia)
Keynote talks:
- Christina Bergmann (The "new" science: transparent, cumulative, and collaborative)
- Jeff Rouder (Modeling individual differences)
- Jennifer Tackett (Thinking Critically and Embracing Uncertainty: Approaches to Theory Specification and Testing in Psychological Science)