Friday , January 22 2021
Home / Lars P. Syll / Big data truthiness

Big data truthiness

Summary:
All of these examples exhibit the confusion that often accompanies the drawing of causal conclusions from observational data. The likelihood of such confusion is not diminished by increasing the amount of data, although the publicity given to ‘big data’ would have us believe so. Obviously the flawed causal connection between drowning and eating ice cream does not diminish if we increase the number of cases from a few dozen to a few million. The amateur carpenter’s complaint that ‘this board is too short, and even though I’ve cut it four more times, it is still too short,’ seems eerily appropriate.

Topics:
Lars Pålsson Syll considers the following as important:

This could be interesting, too:

Lars Pålsson Syll writes Fooled by randomness

Lars Pålsson Syll writes Econometrics and the challenge of regression specification

Lars Pålsson Syll writes How scientists manipulate research

Lars Pålsson Syll writes Econometrics — the art of pulling a rabbit out of a hat

Big data truthinessAll of these examples exhibit the confusion that often accompanies the drawing of causal conclusions from observational data. The likelihood of such confusion is not diminished by increasing the amount of data, although the publicity given to ‘big data’ would have us believe so. Obviously the flawed causal connection between drowning and eating ice cream does not diminish if we increase the number of cases from a few dozen to a few million. The amateur carpenter’s complaint that ‘this board is too short, and even though I’ve cut it four more times, it is still too short,’ seems eerily appropriate.

Lars Pålsson Syll
Professor at Malmö University. Primary research interest - the philosophy, history and methodology of economics.

Leave a Reply

Your email address will not be published. Required fields are marked *