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Where Are We Going with Statistical Computing? From Mathematical Statistics to Collaborative Data Science

Makowski, D., & Waggoner, P. D.

Mathematics, 2023

Statistics, computer science and software development used to be separate trades and are now one activity. This paper traces how statistical computing got there — the open movement, data science, collaborative problem-solving, machine learning and newly accessible Bayesian estimation — and what follows for the field.

Abstract

The field of statistical computing is rapidly developing and evolving. Shifting away from the formerly siloed landscape of mathematics, statistics, and computer science, recent advancements in statistical computing are largely characterized by a fusing of these worlds; namely, programming, software development, and applied statistics are merging in new and exciting ways. There are numerous drivers behind this advancement, including open movement (encompassing development, science, and access), the advent of data science as a field, and collaborative problem-solving, as well as practice-altering advances in subfields such as artificial intelligence, machine learning, and Bayesian estimation. In this paper, we trace this shift in how modern statistical computing is performed, and that which has recently emerged from it. This discussion points to a future of boundless potential for the field.

• DOI: 10.3390/math11081821
• Full text (PDF)

Keywords: Statistical Methods · Open Science · Software Development

Cite

Makowski, D., & Waggoner, P. D. (2023). Where Are We Going with Statistical Computing? From Mathematical Statistics to Collaborative Data Science. Mathematics. https://doi.org/10.3390/math11081821

See also

• Check your outliers! An introduction to identifying statistical outliers in R with easystats — Thériault, R., Ben-Shachar, M. S., Patil, I., Lüdecke, D., Wiernik, B. M., & Makowski, D. (2024)
• The psycho Package: an Efficient and Publishing-Oriented Workflow for Psychological Science — Makowski, D. (2018)
• datawizard: An R Package for Easy Data Preparation and Statistical Transformations — Patil, I., Makowski, D., Ben-Shachar, M. S., Wiernik, B. M., Bacher, E., & Lüdecke, D. (2022)