Data science as an atomic habit
The most important habits are small and consistent, whose benefits slowly build and compound over time.
Writing on open-source data science.
Posts about data analysis, modeling, package development, causal inference, and more. To see my full archive of blog posts prior to 2023, check out this repository.
Estimating sample size for precision: precisely 0.1.0
Introducing precisely, a study planning tool to calculate sample size based on precision rather than power.
Tidy causal DAGs with ggdag 0.2.0
Learn about new features and looks in the ggdag package for making and analyzing causal DAGs.
Introducing the partition package
Introducing partition, a fast and flexible data reduction framework that minimizes information loss and creates interpretable clusters.
Why should I use the here package when I'm already using projects?
here is one of the many tools in our toolkit for addressing reproducibility. It's designed to work with RStudio projects from the root directory up, making it convenient to organize both your files and your file paths.