Welcome to the fifty third ever issue of Monday Morning Data Science from the Fred Hutch Data Science Laboratory. We are excited to show you what we have been working on (Fresh from the Lab), plus links that we think you would be interested in (Our Weekly Bookmarks Bar). Part of the purpose of this newsletter is to start conversations, so if you have a question or there is something you would like to share with us please let us know by responding directly to this email.
Fresh from the Lab
[From the Archives: Jeff Leek on the Frontmatter Podcast] In this Leanpub Podcast, Len Epp interviews Jeff Leek. They discuss Jeff's journey into biostatistics, his work, and experiences with Leanpub, focusing on his book "The Elements of Data Analytic Style," which addresses often overlooked aspects of data analysis. Additionally, they talk about the impact and evolution of data science and biostatistics in modern society, as well as Jeff's contributions to educating a broader audience through online platforms.
Our Weekly Bookmarks Bar
[How to Get Good with R?] In his blog post "How to Get Good with R?", Nicholas Tierney discusses improving R programming skills through two perspectives: coding and non-coding aspects. He offers practical advice for coding, such as naming consistency, style guides, and function writing, and plans to address non-coding elements in a future post.
[An international consensus on effective, inclusive, and career-spanning short-format training in the life sciences and beyond] This paper addresses the challenges in short-format training (SFT) within science, technology, engineering, mathematics, and medicine fields, offering 14 recommendations developed by an international group of experts. These recommendations, guided by "The Bicycle Principles" framework, aim to enhance the effectiveness, inclusiveness, and accessibility of SFT, aligning with educational change theories to overcome systemic barriers.
As always you can contact us by replying directly to this email, you can contact the Data Science Lab at data@fredhutch.org, or you are welcome to join us on the Fred Hutch Data Slack Workspace. For more information about the Fred Hutch Data Science Lab, visit our website: https://hutchdatascience.org/. See you next week!
- The Fred Hutch Data Science Laboratory