The "Practical Data Science for Stats" Collection contains preprints focusing on the practical side of data science workflows and statistical analysis. Curated by Jennifer Bryan and Hadley Wickham.
There are many aspects of day-to-day analytical work that are almost absent from the conventional statistics literature and curriculum. And yet these activities account for a considerable share of the time and effort of data analysts and applied statisticians.
The goal of this collection is to increase the visibility and adoption of modern data analytical workflows.
We aim to facilitate the transfer of tools and frameworks
- between industry and academia
- between software engineering and Stats/CS
- across different domains
While these preprints have not been reviewed by PeerJ, they have been reviewed for content by the editors listed above and peers. We are making them available here at PeerJ to facilitate the broadest access possible. Versions of these articles are also under review for a special issue of The American Statistician, an established venue in the academic community for general-interest articles on statistical practice and teaching.