Our love of dichotomizing

I made a quick list of about 50 blog topics and it’s so hard to know where to start! This one came up in everyday conversation a couple of times for me yesterday (in non-statistical contexts), and I think it is a fundamental aspect underlying what I see to be mis-uses and mis-characterizations of statistical inference in Science and decision making. I also believe it is a substantial root underlying so many other of problems in the world. Right or Wrong. Blue or Red. Significant or Not Significant. Where is the acknowledgment of the gray area between two extremes — where most things lie?

Humans are uncomfortable with the gray area. Humans want answers and strong opinions, and expect each other to give them. Somehow, the use of statistical inference in science evolved over the last 70 decades or so to become a way of taking information from data with its inherent uncertainty and dichotomizing it into “yes” or “no”, or “significant” or “not significant.” I am oversimplifying a little here (but not as much as a I wish I was). Instead of embracing the idea of quantifying a particular type of uncertainty under a set of assumptions and then wrestling with how to use that information relative to a scientific problem, we greatly oversimplify the context by applying inadequately justified thresholds and pretending as if we have a yes or no answer. This is engrained in scientific culture — and now other cultures based on data as well. Every scientist and data user should ask themselves questions: Why do I feel the need for a yes or no answer? Is that really an appropriate end point for this work? Am I oversimplifying? Am I potentially misleading others by presenting the results in the context of a dichotomy? Is this how statistical inference was developed to be used?

I leave these questions out there for now — so much to dig into in future posts. For this post, I just ask you to simply pay attention to when you desire to dichotomize (or categorize in general) when perhaps it’s not justified, or even needed. What is your motivation? Even if it makes a task or discussion more challenging, can you try to get around it and embrace the gray area?