1470. D’ya Like DAGs? A Survey on Structure Learning and Causal Discovery 1471. Custom Discrete Color Scales for ggplot2 1472. A New Coefficient of Correlation 1473. Ten simple rules for teaching yourself R 1474. The case for variable labels in R 1475. Fooled by beautiful data: Visualization aesthetics bias trust in science, news, and social […]
Category: statistics
How to improve your figures #11: Do not repeat information
Do not repeat information in your visualisations. I repeat: Do not repeat information in your visualisations. Space is limited when you visualise data, and you need to make sure that every pixel is worth the space. If you repeat information in a figure, you are most likely using certain defaults and not repeating information consciously […]
Uber and irresistibly interesting data
The other day, the Guardian could report that Uber paid Alan Krueger $100,000 for a study that was positive towards Uber. The fact that the study was positive towards Uber should come as no surprise. You do not pay a lot of money for a study showing that your business is bad for the world. […]
The liar paradox in self-reported survey data
The liar paradox is the logical paradox in the statement “I am lying”. If you are telling the truth about lying, are you then indeed lying? I have been thinking about this paradox and how it might also be relevant for survey research with implications for our understanding of measurement error and the interpretation of […]
Potpourri: Statistics #87
1420. Statistical Control Requires Causal Justification 1421. Graphic Design with ggplot2: How to Create Engaging and Complex Visualizations in R 1422. ggplot2 Wizardry: My Favorite Tricks and Secrets for Beautiful Plots in R 1423. Deep Learning of Potential Outcomes 1424. Six tips for better spreadsheets 1425. Principal Component Analysis (PCA) from Scratch 1426. US Election […]