Potpourri: Statistics #59

Quantitative Politics with R (version Nov 29)
Why scientists need to be better at data visualization
Coding habits for data scientists
Reducing frictions in writing with R Markdown for html and pdf
Reconstructing Images Using PCA
A ggplot2 Tutorial for Beautiful Plotting in R
(Re)introducing skimr v2 – A year in the life of an open source R project
Streetmaps
Survey Weights in R
Introducing BFpack
Another Book on Data Science
Another mixed effects model visualization
Data Science for Lawyers

Potpourri: Statistics #57

Keep It Together: Using the tidyverse for machine learning
Learn to purrr
Mastering Shiny
A Comprehensive List of Handy R Packages
The challenges of using machine learning to identify gender in images
How is polling done around the world?
How to Get Better at Embracing Unknowns
Drawing maps in R
Potential Outcome and Directed Acyclic Graph Approaches to Causality: Relevance for Empirical Practice in Economics
Visualizing Locke and Mill: a tidytext analysis
Tutorial: Cleaning UK Office for National Statistics data in R
– Transitioning into the tidyverse: part 1, part 2
Your Friendly Guide to Colors in Data Visualisation
Optimising your R code – a guided example
Learning data visualization
Reference Collection to push back against “Common Statistical Myths”
mutate_all(), select_if(), summarise_at()… what’s the deal with scoped verbs?!
Tools for Exploring and Comparing Data Frames
Tom’s Cookbook for Better Viz
Themes to Improve Your ggplot Figures
Lesser Known R Features
What Statistics Can and Can’t Tell Us About Ourselves
A Graphical Introduction to tidyr’s pivot_*()
n() cool #dplyr things
Bayesian Linear Mixed Models: Random Intercepts, Slopes, and Missing Data
Prepping data for #rstats #tidyverse and a priori planning
NYT-style urban heat island maps

Potpourri: Statistics #56

Hands-on Machine Learning with R
The Truth About Linear Regression
Data Viz Book Reviews
Make Multi-point “dumbbell” Plots in ggplot2
Storyline
City Intelligence Data Design Guidelines
shinyApp(), runApp(), shinyAppDir(), and a fourth option
Reordering and facetting for ggplot2
R Docker tutorial
S4: a short guide for the perplexed
Introducing trendyy
R you ready to make charts?
Ten more random useful things in R you may not know about
Testing statistical software
Tidy Data Science Workshop
Using tidyverse tools with Pew Research Center survey data in R
A Gentle Introduction to tidymodels
Changing Glyph in legend in ggplot2
Practical Data Science: an introduction to the PeerJ collection

Potpourri: Statistics #54

A data.table and dplyr tour
Mistakes, we’ve drawn a few
Twenty rules for good graphics
gganimate: The grammar of animation
Visualising Intersecting Sets Of Twitter Followers
Docker and Packrat
Explore your Researcher Degrees of Freedom
Teaching material: Data analytics and visualization
10 things R can do that might surprise you
Scraping Data from the Web with rvest
Common statistical tests are linear models (or: how to teach stats)
8 Useful R Packages for Data Science You Aren’t Using (But Should!)
Easy multi-panel plots in R using facet_wrap() and facet_grid() from ggplot2
Winners of the 1st Shiny Contest
Rachael’s R Tutorials
Web Scraping for Broad City Charts
Implementing the super learner with tidymodels
Three things to know beyond base R

Potpourri: Statistics #53

Why so much hate against propensity score matching?
R for Political Data
Data Science Foundations: Know your data. Really, really, know it
P-values 101: An attempt at an intuitive but mathematically correct explanation
Merging Comparative Manifesto Project and ParlGov cabinet composition data at the party-level
Choropleth maps with R – the Belgian edition
Web Data Scraping
Interpretable Machine Learning: A Guide for Making Black Box Models Explainable
Chidi’s budget and utility: doing algebra and calculus with R and yacas
FR2E: Intro to R Using Afrobarometer Data
The New Heuristics
You Need to Start Branding Your Graphs. Here’s How, with ggplot!

R Screencast Tutorials (from Quantitative Social Science Data with R: An Introduction):
Introduction to R and R Studio
Finding Data
Data Management
Variables & Manipulation
Univariate & Descriptive Statistics
Visualising Data
Hypothesis Testing
Bivariate Analysis
Linear Regression & Model Building
OLS Assumptions & Diagnostic Testing
Putting it all Together

Potpourri: Statistics #52

Here’s why 2019 is a great year to start with R: A story of 10 year old R code then and now
How the BBC Visual and Data Journalism team works with graphics in R
Special Topics in Data Science: Responsible Data Science
Causal Data Science
From Psychologist to Data Scientist
Causal Graphs Seminar
R Coding Style Guide
Explaining the 2016 Democratic Primary with Machine Learning
A guide to making your data analysis more reproducible
Exploring the multiplication table with R
hcandersenr: An R Package for H.C. Andersens fairy tales
Solving the model representation problem with broom
Basic Stata Syntax Workshop
Bayesian Logistic Regression using brms, Part 1
Half a dozen frequentist and Bayesian ways to measure the difference in means in two groups
Understanding propensity score weighting
Causal Inference Book
15 new ideas and new tools for R gathered from the RStudio Conference 2019
Keeping up to date with R news
tidylog

Potpourri: Statistics #51

– 2018 in Graphics: Bloomberg, FiveThirtyEight, Reuters, Nathan Yau
Survey Raking: An Illustration
textrecipes 0.0.1
Topics in Econometrics: Advances in Causality and Foundations of Machine Learning
Learning Statistics with R
EDUC 263: Introduction to Data Management Using R
Practical R for Mass Communication and Journalism: How Do I? …
Text classification with tidy data principles
Easily generate information-rich, publication-quality tables from R
gganimate: Getting Started
Text as Data
A biased tour of the uncertainty visualization zoo

Potpourri: Statistics #50

Generating data to explore the myriad causal effects that can be estimated in observational data analysis
A Practical Guide to Mixed Models in R
Ask the Question, Visualize the Answer
Statistical Rethinking with brms, ggplot2, and the tidyverse
Twitter, political ideology & the 115th US Senate
You Can’t Test Instrument Validity
Introduction to Econometrics with R
Hands-On Programming with R
Tidytext Tutorials
What’s the best way to learn the programming language R? (Preferably, for free)

Potpourri: Statistics #49

QuantText: A text-as-data page for political science research
pollofpolls: R package for calculating poll of polls
Best of the visualisation web… June 2018
Custom themes in ggplot2
DeclareDesign: Declaring and Diagnosing Research Designs
A personal essay on Bayes factors
Readings on Visualizing Uncertainty
p-hacker: Train your p-hacking skills!
Data Wrangling Part 1: Basic to Advanced Ways to Select Columns
Data Wrangling Part 2: Transforming your columns into the right shape
Data Wrangling Part 3: Basic and more advanced ways to filter rows
Data Wrangling Part 4: Summarizing and slicing your data
Label line ends in time series with ggplot2
How good is “good”?
The hacker’s guide to uncertainty estimates