Potpourri: Statistics #69

Hands-On Data Visualization: Interactive Storytelling from Spreadsheets to Code
Reflecting on “Vote Cones”
Least squares as springs
Applying PCA to fictional character personalities
Bayes Rules! An Introduction to Bayesian Modeling with R
tiktokr: An R Scraper for Tiktok
Efficient and beautiful data synthesis: Taking your tidyverse skills to the next level
A Gentle Introduction to Tidy Model Stacking
11 Short Machine Learning Ethics Videos
Your first R package in 1 hour
What is a dot plot?
JavaScript for R
Literature on Recent Advances in Applied Micro Methods
In Fallout Over Polls, ‘Margin of Error’ Gets New Scrutiny
Programming Choice Experiments in Qualtrics
The list of 2020 visualization lists
The 9 concepts and formulas in probability that every data scientist should know
Collapse repetitive piping with reduce()
Economics charts in R using ggplot2
Top 10 tips to make your R package even more awesome
Running R Scripts on a Schedule with GitHub Actions
Leveraging labelled data in R
Creating and using custom ggplot2 themes
Advanced R Course
The intuition behind averaging
Underrated Tidyverse Functions
Bullet Chart Variants in R
Using the tidyverse with Databases – Part I


Previous posts: #1 #2 #3 #4 #5 #6 #7 #8 #9 #10 #11 #12 #13 #14 #15 #16 #17 #18 #19 #20 #21 #22 #23 #24 #25 #26 #27 #28 #29 #30 #31 #32 #33 #34 #35 #36 #37 #38 #39 #40 #41 #42 #43 #44 #45 #46 #47 #48 #49 #50 #51 #52 #53 #54 #55 #56 #57 #58 #59 #60 #61 #62 #63 #64 #65 #66 #67 #68

Assorted links #2

31. Stanley Milgram and the uncertainty of evil
32. Electric Schlock: Did Stanley Milgram’s Famous Obedience Experiments Prove Anything?
33. LinkedIn’s Alternate Universe
34. Who Did J.K. Rowling Become?
35. The economics of Christmas trees
36. How To Understand Things
37. On The Exciting Subject Of Earwax And Unsupported Medical Arguments
38. The real David Attenborough
39. The UX of LEGO Interface Panels
40. 99 Good News Stories From 2020 You Probably Didn’t Hear About
41. Memos
42. The Observer Effect – Daniel Ek
43. The economics of vending machines

And here is a list with a few good Twitter threads:

44. Something I’ve learned while in law school is about the social construction of crime
45. In 40 tweets I will describe 40 powerful concepts for understanding the world
46. Here are 50 ideas that shape my worldview
47. Thread on creating your own CS degree online
48. Lessons from different fields
49. Bastion forts around the world
50. My top 12 favourite perceptual illusions
51. A meta-thread of some of my favourite Twitter threads

And some links to good video essays and clips on YouTube:

52. 4-2: The History of Super Mario Bros.’ Most Infamous Level
53. Exploring the Sonic Cocktail of Beastie Boys’ PAUL’S BOUTIQUE
54. Akira Kurosawa – Composing Movement
55. BOOKSTORES: How to Read More Books in the Golden Age of Content
56. How The Shawshank Redemption Humanizes Prisoners
57. Sexual Assault of Men Played for Laughs – Part 1 Male Perpetrators
58. Van Gogh’s Ugliest Masterpiece
59. The Art Of Sci-Fi Book Covers
60. This Is What a “Second-Person” Video Game Would Look Like


Previous posts: #1

Potpourri: Statistics #68

Rain, Rain, Go away: 137 potential exclusion-restriction violations for studies using weather as an instrumental variable
Awesome R Learning Resources
A Quick Guide for Journalists to the Use and Reporting of Opinion Polls
Mapping congressional roll calls
Fancy Times and Scales with COVID data
Colors via clrs.cc in R
grstyle: Customizing Stata graphs made easy
American political data & R
Best-Practice Recommendations for Defining, Identifying, and Handling Outliers
Likelihood Ratios: A Tutorial
Data Science related quotes
cleanplots: Stata graphics scheme
PLSC 31101: Computational Tools for Social Science
Covid-19: The global crisis — in data
Working with Large Spatial Data in R
PCA tidyverse style
The many Flavours of Missing Values
Introducing RStudio and R Markdown
Tools for Analyzing R Code the Tidy Way
Dive into dplyr (tutorial #1)
The Good, the Bad and the Ugly: how (not) to visualize data
Programatically Generating PDF Reports with the Tidyverse
Building an animation step-by-step with gganimate
“package ‘foo’ is not available” – What to do when R tells you it can’t install a package

Potpourri: Statistics #67

Computational Causal Inference at Netflix
Tools for Ex-post Survey Data Harmonization
How to pick more beautiful colors for your data visualizations
Shiny in Production: App and Database Syncing
Introduction to Causal Inference
An Illustration of Decision Trees and Random Forests with an Application to the 2016 Trump Vote
Key things to know about election polling in the United States
State-of-the-art NLP models from R
Introduction to Stan in R
How to write your own R package and publish it on CRAN
Bayesian Analysis for A/B Testing
Estimating House Effects
Heatmaps in ggplot2
The Taboo Against Explicit Causal Inference in Nonexperimental Psychology
Spreadsheet workflows in R
A beginner’s guide to Shiny modules
Dataviz Interview
10 Things to Know About Survey Experiments
Applying Weights
Creating effective interrupted time series graphs: Review and recommendations
Lasso and the Methods of Causality
How We Designed The Look Of Our 2020 Forecast
Taking Control of Plot Scaling
How to measure spatial diversity and segregation?
10+ Guidelines for Better Tables in R
How maps in the media make us more negative about migrants
Comparing two proportions in the same survey
Quantitative Social Science Methods, I (Gov2001 at Harvard University)
Introduction to Computational Thinking
Creating R Packages with devtools
Introduction to Statistical Learning in R
Textrecipes series: Pretrained Word Embedding

Potpourri: Statistics #66

How To Read 2020 Polls Like A Pro
Visualizing Complex Science
What is machine learning, and how does it work?
Choosing Fonts for Your Data Visualization
Why linear mixed-effects models are probably not the solution to your missing data problems
Outstanding User Interfaces with Shiny
How I Taught Tidymodels, Virtually
How your colorblind and colorweak readers see your colors
Graphic Content: How Visualizing Data Is a Life-or-Death Matter
How to Create Brand Colors for Data Visualization Style Guidelines
The R package workflow
Introducing Modeltime: Tidy Time Series Forecasting using Tidymodels
Tidy Geospatial Networks in R
PCA with Age of Empires II data
A practical guide to geospatial interpolation with R
Oh my GOSH: Calculating all possible meta-analysis study combinations
Rating children’s books with empirical Bayes estimation
Normalizing and rescaling children’s book ratings
Tips from an R Journalist
How to improve your R package
A very short introduction to Tidyverse
purrr: Introduction and Application
Supervised Machine Learning for Text Analysis in R
4 Tips to Make Your Shiny Dashboard Faster
How I share knowledge around R Markdown
Teaching Statistics and Data Science Online
a ggplot2 grammar guide
Five Tidyverse Tricks You May Not Know About
How to build a Tufte-style weather graph in R using ggplot2

Potpourri: Statistics #65

How The Economist presidential forecast works
GESIS Workshop: Applied Data Visualization
Introduction to R – tidyverse
Why Is It Called That Way?! – Origin and Meaning of R Package Names
PMAP 8921: Data Visualization
Visualising Odds Ratio
Exeter Q-Step Resources
tidymodels workflow with Bayesian optimisation
How to Create Dummy Variables in R (with Examples)
Guides for Visualizing Reality
How I Teach R Markdown
Getting machine learning to production
Introducing Pew Research Center’s Python libraries
– Textrecipes series: Term Frequency, lexicons, TF-IDF, Feature Hashing
Reproducible Research Data & Project Management in R
ggplot2 Theme Elements Demonstration
Pulling YouTube Transcripts
Congressional Data in R
Learn tidymodels with my supervised machine learning course
Effectively Deploying and Scaling Shiny Apps with ShinyProxy, Traefik and Docker Swarm

Potpourri: Statistics #64

Tidymodels: tidy machine learning in R
The Seven Key Things You Need To Know About dplyr 1.0.0
Introduction to Data Science
When Is Anonymous Not Really Anonymous?
Empirical Papers for Teaching Causal Inference
Why log ratios are useful for tracking COVID-19
Effect Sizes and Power for Interactions in ANOVA Designs
Why I’m not making COVID19 visualizations, and why you (probably) shouldn’t either
Word Rank Slope Charts
Displaying time series with R
New parsnip-adjacent packages
Exploring tidymodels With Hockey Data
Conducting and Visualizing Specification Curve Analyses
How John Burn-Murdoch’s Influential Dataviz Helped The World Understand Coronavirus
Spatial Aggregation
Bayes’ theorem in three panels
The Evolution of the American Census
How to standardize group colors in data visualizations in R
Calibrating time zones: an early bird or a night owl?
Program Evaluation

Potpourri: Statistics #62

Applied Bayesian Statistics Using Stan and R
Understanding Maximum Likelihood: An Interactive Visualization
Creating MS Word reports using the officer package
Shiny: Add/Removing Modules Dynamically
Pollsters got it wrong in the 2016 election. Now they want another shot.
Webscraping with R – from messy & unstructured to blisfully tidy
Six Things I Always Google When Using ggplot2
RStudio Projects and Working Directories: A Beginner’s Guide
RMarkdown Driven Development: the Technical Appendix
conveRt to R: the short course
Tools and guides to put R models into production
Ways to close backdoors in DAGs
OpenIntro Statistics
Use of the .data and .env Pronouns to Disambiguate Your Tidyverse Code

Potpourri: Statistics #61

Fairness and machine learning
How to Be a Statistical Detective
Overfitting: a guided tour
No Framework, No Problem! Structuring your project folder and creating custom Shiny components
Revisiting the Difference-in-Differences Parallel Trends Assumption: Part I Pre-Trend Testing
The Trouble with Crime Statistics
Data project checklist
Data Science resources
Data Science Resources (not the same as above)
Guide: Typography
NumPy: the absolute basics for beginners
Python built-ins worth learning
A Scientist’s Guide to R: Step 2.1. Data Transformation – Part 1
Real Emojis in ggplot2
The birthday paradox puzzle: tidy simulation in R
Introducing googleCloudRunner – serverless R on Google Cloud Platform

Potpourri: Statistics #60

Mining Social Media (also a good introduction to Python)
All The Economist Graphic Detail visualizations in one convenient PDF
R Cookbook, 2nd Edition
How to use Test Driven Development in a Data Science Workflow
Why are polls from different pollsters so different?
Difference-in-Differences
The list of 2019 visualization lists
– Emil Hvitfeldt’s Package Calendar: 1) datalegreyar, 2) glue, 3) details, 4) carbonate, 5) ymlthis, 6) skimr, 7) gghalves, 8) globe4r, 9) gapminder, 10) reactable, 11) slide, 12) polite, 13) gtrendsR, 14) networkdata, 15) covr, 16) Sparkline, 17) golem, 18) flexdashboard, 19) ggtext, 20) rayrender, 21) devout, 22) highcharter, 23) precommit, 24) styler
Introducing sortable to add drag-and-drop to your shiny apps
You can replicate almost any plot with R
Simulation-based Power Calculations for Conjoint Experiments
Mastering Spark with R
10 Tricks for tidyverse in R
Shiny Apps: Development and Deployment
How to Clean Messy Data in R
10 Levels of ggplot2: From Basic to Beautiful
What They Forgot to Teach You About R