R Markdown: The bigger picture - Garrett Grolemund

Statistics has made science resemble math, so much so that we've begun to conflate p-values with mathematical proofs. We need to return to evaluating a scientific discovery by its reproducibility, which will require a change in how we report scientific results. This change will be a windfall to commercial data scientists because reproducible means repeatable, automatable, parameterizable, and schedulable.

About the Author

Garrett Grolemund

Garrett is the author of Hands-On Programming with R and co-author of R for Data Science and R Markdown: The Definitive Guide. He is a Data Scientist at RStudio and holds a Ph.D. in Statistics, but specializes in teaching. He's taught people how to use R at over 50 government agencies, small businesses, and multi-billion dollar global companies; and he's designed RStudio's training materials for R, Shiny, R Markdown and more. Garrett wrote the popular lubridate package for dates and times in R and creates the RStudio cheat sheets.

Follow on Twitter Visit Website More Content by Garrett Grolemund
Previous Video
R qtl2: Rewrite of a very old R package - Karl Broman
R qtl2: Rewrite of a very old R package - Karl Broman

For nearly 20 years, I've been developing, maintaining, and supporting an R package, R/qtl, for mapping qua...

Next Video
R in production - Mark Sellors
R in production - Mark Sellors

With the increase in people using R for data science comes an associated increase in the number of people a...