R Markdown: The bigger picture

Statistics has made science resemble math, so much so that we've begun to conflate p-values with mathematical proofs.

rstudio::conf 2019 publication

R Markdown: The bigger picture

January 25, 2019

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.

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About the speaker

Garrett Grolemund
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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 cheatsheets.