The reference class problem has plagued thinkers for centuries, but as probability and statistics become part of everyday parlance, the issue becomes even more prescient. If we want to draw valuable conclusions, we must take the self out of statistics, writes Aubrey Clayton. 

The COVID-19 pandemic has, sadly, made armchair epidemiologists and statisticians of us all. Just to understand the daily news, people with little or no previous expertise have had to quickly become conversant in technical argot including terms like “basic reproduction number (R₀),” “positive predictive value,” and “case fatality rate,” among others. Predictably, the introduction of this vocabulary of ideas to the general public has also invited a number of rookie mistakes and elementary fallacies. For example, supposing a particular test for the novel coronavirus had a 99% specificity rate, meaning 99 out of every 100 truly virus-free people will test negative, what is the chance that someone who tests positive actually has the virus? If, before attempting an answer, you don't immediately think to ask what the overall incidence rate of the virus is in the population, then you have committed a well-worn fallacy called Base Rate Neglect.