This repository is more or less a list of other repos and the associated slides and docs that are specific to workshops or talks I've given. The repos house notes/slides/code/data etc. They are roughly in chronological order based on when they were given/created/updated, and I link to the repo and associated doc.
Easy Bayes with rstanarm and brms
This workshop provides an overview of the rstanarm and brms packages. Basic modeling syntax is provided, as well as diagnostic checking, model comparison, and how to get more from the models.
Introduction to R Markdown: This workshop introducing @R Markdown and related tools, with an eye toward reproducible research. The document may be found here. The content includes: basic concepts regarding literate programming and reproducible research, how to get started quickly with standard documents, customization and configuration, etc.
Data Processing and Visualization: This workshop focuses on using using various R packages for some of the most common tasks.
Text Analysis with R: A gentle introduction to dealing with text in R.
Mixed Models with R: Workshop outlining basics of mixed models with R.
Graphical and Latent Variable Modeling: This doc provides the source for the workshop on structural equation modeling.
My God, it's full of STARs! Using astrology to get more from your data.: A workshop introducing generalized additive models and related.
Become a Bayesian in 10 Minutes: Talk aimed at giving an introduction Bayesian modeling in R via the Stan programming language.
Engaging the Web with R: Using R for web scraping, extracting data via an API, interactive web-based visualizations, and producing web-ready documents.
Going further with RStudio: Using RStudio for more than scripting.
Ceci n’est pas une %>%: Exploring Your Data with R: This workshop focuses on using magrittr and dplyr.
Data Science Skills Series See Kerby Shedden's notes. These notebooks provide R versions of the Python examples therein. (under development)
R bootcamp: A day long R course given some time ago (2015-08), and perhaps to be given again in the future.
These are in very early stages or not even started yet.
BigR (under development, not yet begun)
An overview of possible approaches to dealing with big data in R.