As the old saying goes — there’s lies, damned lies, and statistics.
There are always multiple ways to collect and analyze data , and there are benefits and limitations to every method.
Moreover, the numbers only tell us so much. Indeed, we often learn more about we don’t know than anything else. The great irony of statistics is there is always so much to talk about with the slightest of information!
Data science — and it’s many disciplinary applications — is really the study of uncertainty.
We’ve gotten pretty good at measuring and even predicting uncertainties, but we’re not too good (as a whole) at communicating those uncertainties to general audiences. This is a problem in the best of times, a disaster in pandemic times.
While the scientists among us are exploring the SARS-COV-2 and COVID-19 data for ourselves and drawing our conclusions, the general public has to rely on daily dashboards and “official” interpretations.
What happens when the official interpretation is wrong?
Thanks for posing and exploring the question.
As a health professional, data scientist, educator, and global citizen, I appreciate it!