Interpreting Data

Two people can look at the same data and reach completely opposite conclusions.

Take my gym, for example.

The gym has been ridiculously crowded for the past few weeks (ironically, I rarely get there any more because I am so busy). The gym is not inexpensive.

What conclusion can one reach about the economy from the fact that the gym has been very crowded?

One person could conclude that the economy must be robust since so many people are able to afford gym membership. He would, of course, be wrong.

The right conclusion is that businessmen and women are not busy so they have time to go to the gym. They have always had gym memberships but are only now using them during business hours. This does not bode well for the economy for at least the next six months since deals take a while to get done and people are getting buff rather than doing deals.

(Of course, in a few months, when the gym starts getting much less crowded, two more conclusions could be reached. First, people are busy again so things are looking up. Or, conversely, people are getting fired so they no longer have their company-paid gym memberships. Only time will tell which one it will be).