hahaha...that's excellent, Susan.
I see some people who are afraid of statistics, sorta like censorship. That's unfortunate because statistics are a powerful ally for evidence-based decision making.
The thing to keep in mind is that statistics are estimates that describe trends in large numbers of people. Statistics cannot be used to predict what will actually happen to an individual...that would be called an anecdote.
I've posted here before this perspective that at it's most basic level, “what statistics tell you is whether you’re in a great big fight, a medium-sized fight, or a little fight. People win and lose all three, so it just tells you what your fighting mind-set is.”
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Here's a thought-provoking use of statistics I recently saw online:
“Imagine you are one of 100 men in a room,” [Newman] says. “Seventeen of you will be diagnosed with prostate cancer, and three are destined to die from it. But nobody knows which ones.” Now imagine there is a man wearing a white coat on the other side of the door. In his hand are 17 pills, one of which will save the life of one of the men with prostate cancer. “You’d probably want to invite him into the room to deliver the pill, wouldn’t you?” Newman says.
Statistics for the effects of P.S.A. testing are often represented this way — only in terms of possible benefit. But Newman says that to completely convey the P.S.A. screening story, you have to extend the metaphor. After handing out the pills, the man in the white coat randomly shoots one of the 17 men dead. Then he shoots 10 more in the groin, leaving them impotent or incontinent.
Newman pauses. “Now would you open that door?” He argues that the only way to measure any screening test or treatment accurately is to examine overall mortality. That means researchers must look not just at the number of deaths from the disease but also at the number of deaths caused by treatment.
That's what the recently published PIVOT study does...