15 new articles on statistical workflow!

Aki, Richard, Lizzie, and I put together a special issue on Statistical Workflow for the Philosophical Transactions of the Royal Society. I guess “royal” isn’t as impressive as it used to be, but still. Statistics and data analytics play an increasingly important role in and across science and policy. But much of what is done by the best practitioners–their “workflow”–is tacit knowledge only glanced over in textbooks and research articles. In this new collection covering a wide range of disciplines, leading statisticians and researchers discuss the motivations and details for their workflows. The four of us did this project because we were all interested in Bayesian workflow, and we wanted to learn more about statistical workflow in general, not just the Bayesian part. Here’s what’s in the issue: Statistical workflow, by Andrew Gelman, Aki Vehtari & Richard McElreath Unsupervised machine learning for scientific discovery: workflow and best practices, by Andersen Chang, Tiffany M Tang,…