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Generalized Additive Models
Join us for the Fitting Models to Data Not Data to Models workshop series! This workshop series introduces early-career researchers to statistical models beyond linear models, focusing on fitting models to data rather than forcing data to fit model assumptions. Sessions use R and RStudio; prior experience is helpful but not required - beginners are encouraged to review R Fundamentals for Data Analysis or attend the intro workshop.
Generalized Additive Models: This workshop will introduce Generalized Additive Models (GAMs), which allow one to fit models that are complex and nonlinear but easily interpretable, unlike many “black-box” machine learning models. By the end of this session, participants will be able to fit GAMs in R using the mgcv package and understand the advantages of GAMs over GLMs and LMs.
Questions? Please reach out to the Centre for Scholarly Communication at csc.ok@ubc.ca.
A full schedule of workshops can be found at csc.ok.ubc.ca/workshops/