We made it to one hundred. I guess this will be the final post in the series. It is good to end the series on a round number. As I have explored ways to blog less in 2023, this seems like as good a time as any to end this particular series of posts. I wrote the first post more than a decade ago as an easy way to bookmark material related to statistics that I would like to share and save for future reference. In the future, I plan to update my awesome-statistics repository on GitHub with relevant material.
1978. Data Vis Dispatch: September 5, September 12, September 19, September 26, October 10, October 17, October 24, October 31
1979. Tidy evaluation in R – Simple Examples
1980. Writing better R functions: part one, part two, part three, part four
1981. Hugging Face, with a warm embrace, meet R️
1982. Geographic data analysis in R and Python: comparing code and outputs for vector data
1983. Exploring Interaction Effects and S-Learners
1984. Making Large Language Models work for you
1985. R for Sign Language Linguistics
1986. How adding a ‘Don’t know’ response option can affect cross-national survey results
1987. Engineering Production-Grade Shiny Apps
1988. What This Graph of a Dinosaur Can Teach Us about Doing Better Science
1989. How to add annotations in ggplot: should you use geoms or annotations?
1990. The Causal Cookbook: Recipes for Propensity Scores, G-Computation, and Doubly Robust Standardization
1991. Generative AI exists because of the transformer
1992. An introduction to Python for R Users
1993. Guide to understanding the intuition behind the Dirichlet distribution
1994. Overview of R Modelling Packages
1995. The problem with “select-all-that-apply” survey questions, graphed
1996. Confidence Intervals in Election Polling: Understanding the Uncertainty of Political Forecasting
1997. Connected Scatterplots Make Me Feel Dumb
1998. Causality for Machine Learning
1999. Creating typewriter-styled maps in {ggplot2}
2000. An overview of what’s out there for reproducibility with R
2001. A Dataset for Violence Trends in the Ancient Middle East between 12,000 and 400 BCE
2002. Geospatial Data Science with Julia
2003. Remind readers of the colors in your data visualization
2004. Introduction to Econometrics with R
2005. Getting Started with Large Language Models: Key Things to Know
2006. How to add annotations in ggplot: should you use geoms or annotations?
2007. Visualizations on Statistics and Signal Processing
2008. Embeddings: What they are and why they matter
2009. The 6 most popular R packages for Dataviz
2010. Spice up your {gt} table with {ggplot}
2011. HCS 7100: Data Visualization in R
2012. What’s New in tidymodels
2013. Approaches to Calculating Number Needed to Treat (NNT) with Meta-Analysis
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