Coronavirus has caused a data deluge. Everywhere we look, statistics abound, among them counts of confirmed cases, number of jobs lost, the declining price of oil, and the vast sums governments are spending to preserve their economies.
I have dedicated my life to the analysis and communication of data, and still I find myself constantly confused. Are the numbers we have on the virus’s trajectory meaningful if so many people have asymptomatic cases? Can we possibly measure the impact of coronavirus on the job market if fewer people are answering surveys at the moment? Can I actually get oil for free now?
Of course, it’s not just because of coronavirus that interpreting data is challenging. Numbers reported by policymakers, academics and the media have always been estimates of what we really want to know—estimates that invariably need caveats. But understanding the strengths and weaknesses of data feels particularly important right now. More than ever, how we interpret statistics could cost people’s lives or livelihoods.