Hannah Fry, for The New Yorker, describes the puzzle of Statistics to analyze general patterns used to make decisions for individuals:
There is so much that, on an individual level, we don’t know: why some people can smoke and avoid lung cancer; why one identical twin will remain healthy while the other develops a disease like A.L.S.; why some otherwise similar children flourish at school while others flounder. Despite the grand promises of Big Data, uncertainty remains so abundant that specific human lives remain boundlessly unpredictable. Perhaps the most successful prediction engine of the Big Data era, at least in financial terms, is the Amazon recommendation algorithm. It’s a gigantic statistical machine worth a huge sum to the company. Also, it’s wrong most of the time.
Be sure to read this one. I especially liked the examples used to explain statistical concepts that sometimes feel mechanical in stat 101.