Potpourri: Statistics #99

Sep 1, 2023 Updated on Oct 25, 2026
  1. Data Vis Dispatch: August 1, August 8, August 15, August 22, August 29

  2. Explainable AI: Visualizing Attention in Transformers

  3. Linear Programming in Python

  4. It Takes Long to Become Gaussian

  5. Cookbook Polars for R

  6. Package development lifecycle process: What does superseded mean? / What does deprecated mean?

  7. Difference-in-differences, Average Treatment Effects and the Importance of Mechanisms: Part 1, Part 2

  8. How I Set Up RStudio for Efficient Coding

  9. Catching up on the weird world of LLMs

  10. Introduction to Educational and Psychological Measurement Using R

  11. Reducing clutter with an options object

  12. Introducing Shannon Regression: An Information Theoretic Alternative to Logistic and Probit Regression for Binary Outcomes

  13. It’s the interactions

  14. Using flexdashboard to create a GitHub Actions-powered YouTube feed

  15. R Functions for Getting Objects

  16. Building Serverless Shiny Apps with webR: A Step-by-Step Guide

  17. Boost Model Performance with Hyperparameter Tuning in R | Tidymodels

  18. Neyman causal model or Rubin causal model?

  19. Teaching the tidyverse in 2023

  20. How to improve the substantive interpretation of regression results when the dependent variable is logged

  21. Dot-dot-dot, bang-bang-bang, and do.call()

  22. The ultimate practical guide to multilevel multinomial conjoint analysis with R

  23. Mixed Models with R

  24. How to Create Your Own Table Theme with the gt Package

  25. How to use UNHCR’s refugees R package

  26. Manually generate predicted values for logistic regression with matrix multiplication in R

  27. Top 10 errors in R and how to fix them

  28. Ordinal Models for Paired Data

  29. Equivalence Tests Using {marginaleffects}

  30. Announcing Python in Excel: Combining the power of Python and the flexibility of Excel

  31. A collection of stand-alone Python machine learning recipes

  32. How to use LLMs for Text Analysis

  33. Wizard's Guide to Statistics

  34. Exploring Causal Discovery with gCastle through Reticulate in R

  35. Recreate a real-world, complex dataviz with R & ggplot

  36. How to design a useful (and fun!) color key for your data visualization

  37. Yet Again: R + Data Science

  38. Is probability frequentist or Bayesian?

https://erikgahner.github.io/posts/feed.xml