… are made up on the spot. A common myth that is deeply rooted in the truth that we really like to make up numbers when talking about things. I don’t think hardly anyone can say that they haven’t at some point or another described themselves as being 99% sure or quoted data in an approximate percent form just to prove a point about something. What is strange about all this is that as good as we can be about seeing through bad numbers when someone is describing them (though lets be real a trusted person throwing numbers at you can be particularly tricky), we have a really hard time seeing that data is bad or somewhat wrong when they are given in official looking studies or through visuals.
“We have a natural tendency to trust images more than text.” Randy Olsen brings this important fact to the table to give good reason as to why visuals can fool us so easily, but an entire extra layer when you dig deeper into looking at how you can fool people into believing data. The British Journal of Psychology did a study where they introduced an audience that was split into two groups to a fictional disease and gave them the same data for who got better and who did not, the only difference, one group was given data that a large amount of people tried the experimental remedy and the other was told very few used the remedy. The results of the study came out showing that those who were told that the majority used the remedy believed the remedy helped, while the other group saw through the remedy quite easily.
In a more humorous example this article describes how a journalist posed as a Ph. D and got people to help him do a study to “prove” that that chocolate helps with weight loss. This example is less of an illusion as the previous, but it is similar in that people trusted newspapers and magazines published data that chocolate did indeed cause people to lose weight.
False data is unfortunately all around us, and while I think many of us have become adept at seeing though some of it ultimately the human mind seems to doom us to falling for something every now and again. Likely the only true solution to the problem is to screen published data so that it is valid and reliable, but that cannot happen as it would lead to a whole slew of other problems.