Gary Smith’s advice on statistics, Standard Deviations, is a really useful and entertaining book. In this Smith points out a number of major problems with the way stats are used. Some problems arise from deliberate tricks played by researchers/managers describing data. Other problems arise through carelessness; the researcher/manager using the data doesn’t realize they are abusing the data. Over the next few weeks I’ll examine three problems that Smith highlights. Today I’ll focus on The Secret Axis.
The Secret Axis
One of the problems Smith describes comes from the way that data is visualized. He makes a host of scathing and funny comments about data presentation. I liked his description of “The Secret Axis” (Smith, 2014, page 73) which is something I often see in graphs. (Technically something I don’t see given it is a missing axis).
Smith gives high profile examples of abuse of data visualization. In 1982 Ronald Reagan presented his budget plan with no numbers on the Y-axis. The viewer, therefore, could not know the scale of what was being presented. In the end the president’s team choose to present a 9% difference in tax plans as a 90% difference on the (unspecified) Y-axis. The quote from David Gergen, Reagan’s spokesman is fantastic.
‘”We tried it with numbers and found they were very hard to read on television so we took them off”‘Smith, 2014, page 74.
If we are (very, very) generous we might assume that Gergen made a mistake that just happened to make his boss look better. If we are less generous we might call it deliberate deception. Making your graph meaningless doesn’t help people interpret it.
Be Careful About How You Present Data
The lesson is that we all need to be careful about the way we present data. We don’t want to leave anyone with a false impression because of our secret axis.
Conversely when confronted with a secret axis don’t accept it. What is a graph without a clear axis? Such a graph is merely a pretty picture and should never be treated seriously.
Read: Gary Smith, 2014, Standard Deviations: Flawed Assumptions, Tortured Data and Other Ways to Lie With Statistics, The Overlook Press.