Linear models

…Participants fit and interpret linear models, interactions, generalized linear models and mixed models, learning how to connect analytical choices to data structure and report results clearly. 2027-01-18–2027-01-21, 14:00–19:00 daily, Europe/Berlin (CET, UTC+01:00). Online course; fee €480. Suitable for beginners and early-career researchers; no prior statistics, pr

Conventional approaches to hypothesis testing often hinge on linear models like ANOVA, subjective decision-making regarding factors and their interactions, and reliance on in-sample inference without thorough evaluation on hold-out data. These oversimplifications, subjective choices, and limited generalizability may cast doubt on the relevance and validity of scientific theories and conclusions. A transformative shift towards more resilient methodologies entails the incorporation of interpretability techniques, sophisticated machine learning models, and advanced out-of-sample model evaluation