Should You Trust Your Analytics Model?

Written by: Paul Rubin

Primary Source: OR in an OB World

The short answer is “no”. At least, don’t put too much faith in them.

“Remember that all models are wrong; the practical question is how wrong do they have to be to not be useful.”  (George E. P. Box)

It’s also useful to remember that your model, no matter how sophisticated or how well supported by theory, is calibrated using data that might be a tad suspect.

“The government are very keen on amassing statistics. They collect them, add them, raise them to the nth power, take the cube root and prepare wonderful diagrams. But you must never forget that every one of these figures comes in the first instance from the chowky dar (village watchman in India), who just puts down what he damn pleases.”  (Stamp’s Law)

All that said, there was a very nice entry recently in the HBR Blog Network, “How to Tell If You Should Trust Your Statistical Models“, that is well worth reading. The author is Theodoros Evgeniou, Professor of Decision Sciences and Technology Management at INSEAD. (Tip of the hat to +Aleksandr Blekh for providing the link on Google+.)

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I'm an apostate mathematician, retired from a business school after 33 years of teaching mostly (but not exclusively) quantitative methods courses. My academic interests lie in operations research. I also study Tae Kwon Do a bit on the side.

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