The debate over the value and interpretation of p-value has endured since the time of its inception nearly 100 years ago. The use and interpretation of p-values vary by a host of factors, especially by discipline. These differences have proven to be a barrier when developing and implementing boundary-crossing clinical and translational science. The purpose of this panel discussion is to discuss misconceptions, debates, and alternatives to the p-value.
There was a recent email thread in the IsoStat listserv about a cool visualization that recently came out in the New York Times showing COVID-19 cases over time. This sparked a discussion about whether this was possible to recreate in R with ggplot, so of course I gave it a try!