# 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