Numbers Don’t Lie

by | Feb 5, 2013 | General | 0 comments

Some years back, I came upon an article in the San Francisco Chronicle comparing major airlines’ on-time performance (1).  This comparison was based on data published by the US Department of Transportation on a monthly basis. The article listed the airlines having the best and poorest performance but without any explanation of why that might be. In particular, they ranked Alaska Airlines at the bottom of the list.  As I read the article I realized that the readers would make the erroneous conclusion that Alaska Airlines was doing a very poor job.  Why did I think this conclusion was erroneous?  Because Alaska Airlines flies out of cities prone to extreme weather conditions and these conditions would naturally cause delays.

Confounding Variables

In Statistics, confounding (i.e., lurking) variables are extraneous variables that correlate to the dependent or independent variable.  Failing to recognize these usually leads to erroneous causal conclusions.  In the case of the airlines’ on-time performance article, the article failed to mention that Alaska Airlines flies out of foggy airports.  Therefore, it is highly possible that it is not the airline contributing to the delay but, rather, the airport the airline is flying out of.  I wrote a letter to the editor explaining this (2).

Bottom line: watch out for those lurking variables. People can lie with numbers but numbers don’t lie!

(1) The San Francisco Chronicle article can be found here:
(2) The letter I published can be found here: