Presented Tuesday, March 24th
Good data analysis is reproducible. If someone else can’t independently replicate your results from your data, the consequences can be severe. With R, a challenge for reproducibility is the ever-changing package ecosystem: it's all too easy to develop an R script using packages, only to find collaborators will download later versions of those packages when they attempt to reproduce your results, making outcome unpredictable.
In this talk David will introduce the Reproducible R Toolkit, and the "checkpoint" package, included with Revolution R Open, and describe some best practices for writing reliable, reproducible R code with packages.