Dear all,
It is still possible to join us for our online course on Generalized Linear Models in R in May (6-10).
Course website: https://www.physalia-courses.org/cou...ops/glm-in-r-1
The course is aimed at graduate students and researchers with basic statistical knowledge that want to learn how to analyze experimental and observation data with generalized linear regression models in R. Basic knowledge means that we assume knowledge about foundational statistical concepts (e.g. standard error, p-value, hypothesis testing) that are usually covered in a first introductory statistics class. Participants should also be familiar with Rstudio and have some experience in programming R code, including being able to import, manipulate (e.g. modify variables) and visualize data.
At the end of this course, attendees will be able to:
1. Specify and fit generalized linear regression models in R, choosing the appropriate distribution and link function according for your data.
2. Interpret the parameter estimates of the fitted models, including the correct interpretation of categorical predictors (e.g. contrasts, ANOVA, post-hoc testing), and calculate predictions from your model.
3. Understand the principles of model selection to choose the correct model / regression formula for your question.
4. Visualize the fitted models to check assumptions, communicate results, and increase understanding.
5. Acquire the foundations and some first ideas to move on to more complex regression models (e.g. Generalized Linear Mixed Models, Generalized Additive Models, Bayesian modeling) in the future.
For the full list of our courses and workshops, please visit: https://www.physalia-courses.org/courses-workshops/
Best regards,
Carlo
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Carlo Pecoraro, Ph.D
Physalia-courses DIRECTOR
[email protected]
mobile: +49 17645230846