From time to time, I delve into Darrel Huff's How to lie with statistics published in 1954. I was reading the chapter on 'statistical significance' and came upon this passage which I found relative to today:
"A remarkable instance of this came out in connection with a test of a polio vaccine a few years ago. It appeared to be an impressively large-scale experiment as medical ones go. 450 children were vaccinated in a community and 650 were left unvaccinated , as controls. Shortly thereafter the community was visited by an epidemic. Not one of the vaccinated children contracted a recognizable case of polio.
Neither did any of the controls. What the experimenters had overlooked or not understood in setting up their project was the low incidence of paralytic polio. At the usual rate, only two cases would have been expected in a group this size, and so the test was doomed from the start to have no meaning. Something like fifteen to twenty-five times this many children would have been needed to obtain an answer signifying anything. Many a great, if fleeting, medical discovery has been launched similarly. "Make haste, as one physician put it, "to use a new remedy before it is too late."
The guilt does not always lie with the medical profession alone. Public pressure and hasty journalism often launch a treatment that is unproved, particularly when the demand is great and the statistical background hazy. So it was with the cold vaccines that were popular some years back and the antihistamines more recently. A good deal of the popularity of these unsuccessful 'cures' sprang from the unreliable nature of the ailment and from a deflect of logic. Given time, a cold will cure itself. " p. 42-43.
Sound familiar?
In the book, there's a quote from H.G. Wells: Statistical thinking will one day be as necessary for efficient citizenship as the ability to read and write.
Oh well. So much for that.
People aren't even calculating on their own the death rate into the population during this health crisis. Simple basic statistical exercises have proven too much it would appear.
Happy New Year.
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