Linear Models in R – Part 2
[This article was first published on pacha.dev/blog, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
A step-by-step explanation of how to fit a linear model. Here we cover GLM (Generalized Linear Models) but focus on the Poisson link and work with datasets that we have to download and join to produce a final dataset to explore the effects of distance, contiguity and colonial history on exports.
You can read more about the topics covered in:
- Linear Models with R (https://julianfaraway.github.io/faraway/LMR/)
- R for Data Science (https://r4ds.had.co.nz/relational-data.html#mutating-joins) for the joins part
Code: https://github.com/pachadotdev/youtube-codes/tree/main/2023-07-13-linear-models-part-2
If you like this video and want to keep learning, I organize regular 1-hour workshops and 1:1 tutoring https://www.buymeacoffee.com/pacha/
To leave a comment for the author, please follow the link and comment on their blog: pacha.dev/blog.
R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.