The case of the Morgan Stanley graph
What went wrong with a graph about intensive care in US states?
The Covid-19 pandemic has put great urgency on visualising data and numbers. That flurry leads to some great and poor graphs.
One example of bad graphing appears to come from Morgan Stanley. The graph shows intensive care patients in ‘closed’ and ‘open’ US states. There is a linear smoothing line, with confidence intervals.
I am unable to find the original report. The earliest record was on Twitter, shared by an academic at Yale School of Medicine.
The implicit conclusion is restrictions failed to work, with rising intensive care patients. One key problem is the linear model ‘smoothing’ a clear jump in occupancy numbers.
Where did this discontinuity come from? Analysis by data scientist Tristan Mahr shows later versions do not have this jump.
An archived version shows missing values for the state of New York. Aggregation of these absent stats gives an artificial rise. In essence, the graph treated numbers which were unavailable as zero.
