You may think of R as a tool for complex statistical analysis, but it's much more than that. From data visualization to efficient reporting, to improving your workflow, R can do it all. On this podcast, I talk with people about how they use R in unique and creative ways.
R for the Rest of Us Podcast Episode #26: Nick Tierney
In this episode, I chat with Nick Tierney, a statistician, data scientist, and creator of the {naniar} R package for exploring missing data. Nick reflects on his journey from a psychology undergrad to a PhD in statistics, and how open-source tools—and a deeply curious mindset—shaped his path.
We discuss Nick’s early struggles with R, the importance of community, and his evolution into package development and consulting. He also walks through the why and how of testing R packages, making the case for better, more reliable code.
Resources mentioned:
{naniar} package (https://naniar.njtierney.com/)
Books: (1) The R Book by Michael Crawley, and (2) R Packages by Hadley Wickham and Jenny Bryan
Connect with Garrick on Bluesky (https://bsky.app/profile/njtierney.bsky.social) and GitHub (https://github.com/njtierney)
12 Jun 2025TRANSCRIPT
R for the Rest of Us Podcast Episode #27: Garrick Aden-Buie
Garrick Aden-Buie, a software engineer at Posit, discusses his project brand.yml, which simplifies branding across data science outputs like Quarto documents and Shiny apps in this interview with host David Keyes.
20 Mar 2025TRANSCRIPT
R for the Rest of Us Podcast Episode #25: Robert Smith
In this episode, I sit down with Robert Smith, co-founder of Dark Peak Analytics, to discuss his journey from academia to advising the UK government during the COVID-19 pandemic. Rob shares his experience building data models that directly influenced public health policy and decision-making at the highest levels. We also dive into his work with Parkrun, a community-driven initiative promoting equitable access to physical activity, and how he used R to analyze participation patterns and improve accessibility.
Rob's insights into health economics, simulation modeling, and the challenges of transitioning industries provide valuable lessons for data professionals.
Important resources mentioned:
Dark Peak Analytics (https://darkpeakanalytics.com/)
Academic Papers:
https://wellcomeopenresearch.org/articles/5-9
(https://wellcomeopenresearch.org/articles/5-9)https://www.sciencedirect.com/science/article/pii/S0033350620304066
(https://www.sciencedirect.com/science/article/pii/S0033350620304066)https://www.sciencedirect.com/science/article/pii/S1353829221001222
(https://www.sciencedirect.com/science/article/pii/S1353829221001222)https://link.springer.com/article/10.1186/s12889-024-20420-0
(https://link.springer.com/article/10.1186/s12889-024-20420-0)https://www.medrxiv.org/content/10.1101/19004143v1.full.pdf (https://www.medrxiv.org/content/10.1101/19004143v1.full.pdf)
Map: https://iolmap.shinyapps.io/parkrun/ (https://iolmap.shinyapps.io/parkrun/)
Parkrun (https://www.parkrun.com/)
Connect with Robert on:
LinkedIn: Robert Smith
(https://www.linkedin.com/in/robert-smith-dpa/)
Subscribe to our newsletter: https://rfortherestofus.com/newsletter
Inside a recent episode
R for the Rest of Us Podcast Episode #26: Nick Tierney
Published 10 Jul 2025 · Transcript excerpt
[…] I have created our packages, like we work with clients, we create our packages, but some of my consultants who I work with have written tests, but I've never done it myself. So I'm curious first of all, if you can tell me like, what is a test and what's your spiel for like why it's valuable to write tests when making a package? […]
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