Increasing Reproducibility and Efficiency with R

Abstract

Reproducibility, the ability to reproduce one’s results from the same data and code, and efficiency go hand-in-hand for statistical analyses. The more efficient your code, the easier it is to reproduce your results. When collaborating with others, reproducible and efficient code is even more vital. In R and RStudio, there are many tools available to increase both your efficiency and your reproducibility. In this talk, I will focus on two families of tools: the rmarkdown and the tidyverse suites of R packages. Rmarkdown and related packages make it easy to conduct reproducible research, and the tidyverse programming paradigm helps you write more efficient R code. You will leave this talk with knowledge of at least one new R package to add to your R toolbox and make your research better.

Date
Feb 20, 2020
Location
United States Military Academy
West Point, NY 10996
Sam Tyner-Monroe, Ph.D.
Sam Tyner-Monroe, Ph.D.
Managing Director, Responsible AI

I am an applied statistician and data scientist, with a wide range of skills and experiences. I’m passionate about using data to make a difference.

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