From historians to financial analysts, researchers of all
stripes are interested in prediction. Prediction asks the
question, “given what I know so far, what do I expect will come
next?” In the current political season, presidential election
forecasts abound. This dates back to the work of Ray Fair, whose
book is ridiculously cheap on Amazon. In today’s post, I will
give an example of a much more basic–and hopefully,
relatable–question: given the height of a father, how do we
predict the height of his son? To see how common predictions
about children’s traits are, just Google “predict child
appearance” and you will be treated to a plethora of websites
and iPhone apps with photo uploads. Today’s example is more
basic and will follow three questions that we should ask
ourselves for making any prediction: 1. How different is the
predictor from its baseline? It’s not enough to just have a
single bit of information from which to predict–we need to know
something about the baseline of the information we are interes