How many significant figures should I use?

That question gets asked dozens of times every semester in my statistics classes; it’s pretty clear that most of my students have no sense of scale or proportion about numbers.

But now I have Dr Rhett Alain’s short answer in his Dot Physics Measurement and Uncertainty Smackdown, wherein he refers to the (extremely) long answer in John Denker’s excellent Uncertainty as Applied to Measurement and Calculation.  Why we’re not teaching this in our service courses for science majors, I have no idea.  The Monte Carlo approach described by Alain is a simple application of what statisticians call “bootstrapping,” so perhaps I will start.

Second hand tip from the Geek Press

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