R-sources 📙

Where to go from here

This is just the begining. Here you will find a repository of resources to learn more by topic: statistics, geocomputation, text analysis, building apps, etc.

The joy of learning R is that you can learn anything as long as you put the time. R is free, so is RStudio. Most books on R are also free, and have wonderful online versions you can consult.

Below a list of my favorite online resources on R, click below to see the links for each one:

Bookmark this!

• Statistical Modeling, Causal Inference, and Social Science Blog

• Andrew Heiss’ Blog

• Telling stories with data

• R for Data Science 1st edition and 2nd edition

• Introduction to Data Science

• R Programming for Data Science

• Hands-On Programming with R

• Big Book of R

• Solomon Kurz’s Blog

Mapping

• Geocomputation with R

• Spatial Data Science

• Leaflet for R

Visualisation

• R Graphics Cookbook

• Fundamentals of Data Visualization

• Interactive web-based data visualization with R, plotly, and shiny

• ggiraph book

Text analysis

• Text mining with R

• Supervised Machine Learning for text analysis in R

Publishing

• Quarto

• R Markdown Cookbook

• R Markdown: The Definitive Guide

Shiny

• Mastering Shiny

• Outstanding User Interfaces with Shiny

Causal inference

• Causal Inference: The Mixtape by Scott Cunningham

• The Effect: An Introduction to Research Design and Causality by Nick Huntington-Klein

Statistics

• Statistical rethinking with brms, ggplot2, and the tidyverse: Second edition by Solomon Kurz

• Regression modelling strategies

• Stan User’s Guide

• Bayes Rules! An introduction to applied bayesian modelling

• Tidymodels

• Beyond Multiple Linear Regression

• Statistical Inference via Data Science

• Improving Your Statistical Inferences by Daniel Lakens