1940. Data Vis Dispatch: August 1, August 8, August 15, August 22, August 29

1941. Explainable AI: Visualizing Attention in Transformers

1942. Linear Programming in Python

1943. It Takes Long to Become Gaussian

1944. Cookbook Polars for R

1945. Package development lifecycle process: What does superseded mean? / What does deprecated mean?

1946. Difference-in-differences, Average Treatment Effects and the Importance of Mechanisms: Part 1, Part 2

1947. How I Set Up RStudio for Efficient Coding

1948. Catching up on the weird world of LLMs

1949. Introduction to Educational and Psychological Measurement Using R

1950. Reducing clutter with an options object

1951. Introducing Shannon Regression: An Information Theoretic Alternative to Logistic and Probit Regression for Binary Outcomes

1952. It’s the interactions

1953. Using flexdashboard to create a GitHub Actions-powered YouTube feed

1954. R Functions for Getting Objects

1955. Building Serverless Shiny Apps with webR: A Step-by-Step Guide

1956. Boost Model Performance with Hyperparameter Tuning in R | Tidymodels

1957. Neyman causal model or Rubin causal model?

1958. Teaching the tidyverse in 2023

1959. How to improve the substantive interpretation of regression results when the dependent variable is logged

1960. Dot-dot-dot, bang-bang-bang, and do.call()

1961. The ultimate practical guide to multilevel multinomial conjoint analysis with R

1962. Mixed Models with R

1963. How to Create Your Own Table Theme with the gt Package

1964. How to use UNHCR’s refugees R package

1965. Manually generate predicted values for logistic regression with matrix multiplication in R

1966. Top 10 errors in R and how to fix them

1967. Ordinal Models for Paired Data

1968. Equivalence Tests Using {marginaleffects}

1969. Announcing Python in Excel: Combining the power of Python and the flexibility of Excel

1970. A collection of stand-alone Python machine learning recipes

1971. How to use LLMs for Text Analysis

1972. Wizard’s Guide to Statistics

1973. Exploring Causal Discovery with gCastle through Reticulate in R

1974. Recreate a real-world, complex dataviz with R & ggplot

1975. How to design a useful (and fun!) color key for your data visualization

1976. Yet Again: R + Data Science

1977. Is probability frequentist or Bayesian?

Previous posts: #1 #2 #3 #4 #5 #6 #7 #8 #9 #10 #11 #12 #13 #14 #15 #16 #17 #18 #19 #20 #21 #22 #23 #24 #25 #26 #27 #28 #29 #30 #31 #32 #33 #34 #35 #36 #37 #38 #39 #40 #41 #42 #43 #44 #45 #46 #47 #48 #49 #50 #51 #52 #53 #54 #55 #56 #57 #58 #59 #60 #61 #62 #63 #64 #65 #66 #67 #68 #69 #70 #71 #72 #73 #74 #75 #76 #77 #78 #79 #80 #81 #82 #83 #84 #85 #86 #87 #88 #89 #90 #91 #92 #93 #94 #95 #96 #97 #98