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