– Bayes Rules! An Introduction to Bayesian Modeling with R
– A friendly introduction to machine learning compilers and optimizers
– A History of Polar Area / Coxcomb / Rose charts & how to make them in R’s ggplot2
– A Dataset of Cryptic Crossword Clues
– Survival Analysis: Part I: Basic concepts and first analyses, Part II: Multivariate data analysis – an introduction to concepts and methods, Part III: Multivariate data analysis – choosing a model and assessing its adequacy and fit, Part IV: Further concepts and methods in survival analysis
– Dataviz Accessibility Resources
– RegExplain
– A Succinct Intro to R
– Deep Learning’s Diminishing Returns
– Working with Google Sheets from R
– The Rise of the Pandemic Dashboard
– Predicting FT Trending Topics
– The Art of Linear Algebra: Graphic Notes on “Linear Algebra for Everyone”
– Modeling Possibly Nonlinear Confounders
– ggHoriPlot: build horizon plots in ggplot2
– Finding the Eras of MTV’s The Challenge Through Clustering
– Why data scientists shouldn’t need to know Kubernetes
– Creating a Dataset from an Image in R Markdown using reticulate
– Neural Networks from scratch
– plotDK: Plot Summary Statistics as Choropleth Maps of Danish Administrative Areas
– The Power of Parameterized Reports With Plumber
– Riding tables with {gt} and {gtExtras}
– How to explain gradient boosting
– How to visualize decision trees
– Speech and Language Processing
– Sexy up your logistic regression model with logit dotplots
– AI’s Islamophobia problem
– Possession Is The Puzzle Of Soccer Analytics. These Models Are Trying To Solve It.

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– Investigation of Data Irregularities in Doing Business 2018 and Doing Business 2020
– Dyadic Clustering in International Relations
– Forecasting: Principles and Practice
– Data Disasters
– A Quick How-to on Labelling Bar Graphs in ggplot2
– Data visualisation using R, for researchers who don’t use R
– Easy access to high-resolution daily climate data for Europe
– Put R Models in Production
– Machine learning, explained
– Three ways to visualize binary survey data
– In defense of simple charts
– Modern Statistics with R
– How to avoid machine learning pitfalls: a guide for academic researchers
– Tune xgboost models with early stopping to predict shelter animal status
– Machine-learning on dirty data in Python: a tutorial
– I saw your RCT and I have some worries! FAQs
– Up and running with officedown
– Use racing methods to tune xgboost models and predict home runs
– The 5-minute learn: Create pretty and geographically accurate transport maps in R
– R’s Internal Data Formats: .Rda, .RData, .rds
– Improve Your Code – Best Practices for Durable Code
– An educator’s perspective of the tidyverse
– Estimating regression coefficients using a Neural Network (from scratch)
– Let users choose which plot you want to show
– A look into ANOVA. The long way.
– 3 alternatives to a discrete color scale legend in ggplot2
– Downloading the Census Household Pulse Survey in R
– The Stata Guide
– The Four Pipes of magrittr
– Introducing {facetious} – alternate facets for ggplot2
– Alternatives to Simple Color Legends in ggplot2
– Top 3 Coding Best Practices from the Shiny Contest
– Visualizing ordinal variables
– Making Shiny apps mobile friendly
– Climate circles
– Elegant and informative maps with tmap
– Exploring R² and regression variance with Euler/Venn diagrams
– Exploring Pamela Jakiela’s simple TWFE diagnostics with R
– The marginaleffects package for R
– A lightweight data validation ecosystem with R, GitHub, and Slack
– Create spatial square/hexagon grids and count points inside in R with sf
– A daily updated JSON dataset of all the Open House London venues, events, and metadata
– Animating Network Evolutions with gganimate
– Beyond Bar and Box Plots
– Causal Inference in R Workshop
– Odds != Probability
– How to visualize polls and results of the German election with Datawrapper
– Irreproducibility in Machine Learning
– tidybundestag
– A collection of themes for RStudio
– Shiny, Tableau, and PowerBI: Better Business Intelligence
– Automate PowerPoint Production Using R
– Estimating graph dimension with cross-validated eigenvalues
– Understanding text size and resolution in ggplot2
– Introduction to linear mixed models

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– Introducing pewmethods: An R package for working with survey data
– Exploring survey data with the pewmethods R package
– Weighting survey data with the pewmethods R package
– Analyzing international survey data with the pewmethods R package
– autumn: Fast, Modern, and Tidy Raking
– Data science for economists
– Papers about Causal Inference and Language
– Yale Applied Empirical Methods PHD Course
– Spreadsheet Munging Strategies
– Visual Vocabulary: Designing with data
– What can we learn from a country’s diplomatic gifts?
– Map, Walk, Pivot
– The Epidemiologist R Handbook
– Machine learning with {tidymodels}
– Choose your own tidymodels adventure
– Applied Spatial Statistics with R
– ggplot: the placing and order of aesthetics matters
– Introduction to Functional Data Analysis with R
– Visualizing Distributions with Raincloud Plots with ggplot2
– A Chat with Andrew on MLOps: From Model-centric to Data-centric AI
– ISLR tidymodels Labs
– Plotting maps with ggplot2
– R instructions for our research projects
– A gentle introduction to deep learning in R using Keras
– Everything You Always Wanted to Know About ANOVA
– Replication Materials for “The Flying Bomb and the Actuary” (Shaw and Shaw, 2019)
– Colors and emotions in data visualization
– Rookie R mistakes
– 10 Tips to Customize Text Color, Font, Size in ggplot2 with element_text()
– Writing unit tests in R
– The Good, the Bad and the Ugly: how to visualize Machine Learning data
– A curated list of APIs, open data and ML/AI projects on climate change
– R for SEO
– Using Geospatial Data in R
– Good Data Scientist, Bad Data Scientist
– The Evolution of a ggplot (Ep. 1)
– Do Wide and Deep Networks Learn the Same Things?

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– Monty Hall Simulations
– Making the Monty Hall problem weirder but obvious
– The Intuitive Monty Hall Problem
– The psychology of the Monty Hall problem: Discovering psychological mechanisms for solving a tenacious brain teaser
– The Collider Principle in Causal Reasoning: Why the Monty Hall Dilemma Is So Hard
– Rationality, the Bayesian standpoint, and the Monty-Hall problem
– Josh Miller’s alternative, more intuitive, formulation of Monty Hall problem
– Monty Hall problem solved in tidyverse

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– SDS 375/395 Data Visualization in R
– Demystifying the coalesce function
– Data Viz Bookmarks
– Data Science: A First Introduction
– Crime by the Numbers
– The value of p
– The Tidyverse in a Table
– Sample Size Justification
– Learn tidytext with my new learnr course
– Using random effects in GAMs with mgcv
– Public Policy Analytics: Code & Context for Data Science in Government
– How to run 100 regressions without loops in R
– Spreadsheet mistakes – news stories
– Weights in statistics
– Importing Multiple Files Quickly and Efficiently
– Making Sense of Sensitivity: Extending Omitted Variable Bias
– Microsoft365R: an R interface to the Microsoft 365 suite
– fixest: Fast Fixed-Effects Estimations
– Grab World Bank Data in R with {WDI}
– Lists are my secret weapon for reporting stats with knitr
– Building a team of internal R packages
– Tidyverse Skills for Data Science in R
– Practical Applications in R for Psychologists
– Transform List into Dataframe with tidyr and purrr
– Main terms and concepts in R
– A complete guide to scales
– Computational Thinking for Social Scientists
– A Crash Course in Good and Bad Controls
– Causal design patterns for data analysts
– Modern Data Science with R
– Generating SQL with {dbplyr} and sqlfluff
– Hypothesis test by hand
– How to Use Git/GitHub with R
– Testing for normality
– Scrape Hundreds of PDF Documents From the Web with R and rvest
– Radial Patterns in ggplot2
– a gRadual intRoduction to Shiny
– Reading tables from images with magick
– ggplot Wizardry Hands-On

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