If Bias Is Hardwired Use Statistics to Deal With It

Behavioral economist Dan Ariely discusses how, and why, we cheat in this video. My perspective on this is colored by organizing for a new class of mostly biomedical science PhD students in my experimental statistics course this spring.

These thoughts are much less concerned about them cheating in the course than about ensuring they don't join the ranks of scientists generating results that are shrouded by the mists deception.

Ariely's view is that cheating is an inherent human attribute. That there's simply no denying our proclivity to be deceptive. It is human nature.

Therefore, it makes sense that we all should simply operate with the understanding that scientists are like any other humans. We all suffer from inherent impulses to make our work and ourselves seem a little better than they truly are.

This is just one of the many biases that confront scientists as they go about their work.

Fortunately, we can use a tool that helps us deal with bias in a systematic way.

Experimental statistics is lot of things, It is applied math. It is a variety of models that simplify our data to make them more easy to understand and to explain to others. But at its very core, experimental statistics mostly functions as an abstract machine that helps us control our tendency to deceive others....and, perhaps most importantly, ourselves.