Thinking Statistically

In Thinking Fast and Slow, Daniel Kahneman personifies two modes of thought as System 1 and System 2. System 1 is fast. It takes in information, processes it rapidly, and doesn’t always make us cognizant of the information we took in. It reacts to the world around us on an intuitive level, isn’t good at math, but is great at positioning us for catching a football.

 

System 2 is slow. Its is deliberate, calculating, and uses a lot of energy to maintain. Because it requires so much energy, we don’t actually active it very often, not unless we really need to. What is worse, System 2 can only operate on the information (unless we have a lot of time to pause specifically for information intake) that System 1 takes in, meaning, it processes incomplete information.

 

System 1 and System 2 are important to keep in mind when we start to to think statistically, something our minds are not good at. When we think back to the 2016 US Presidential election, we can see how hard statistical thinking is. Clinton was favored to win, but there was a statistical chance that Trump would win, as happened. The chance was small, but that didn’t mean the models were all wrong when he did win, it just means that the most likely event forecasted didn’t materialize. We had trouble thinking statistically about win percentages going into the election, and had trouble understanding an unlikely outcome after it happened.

 

“Why is it so difficult for us to think statistically?” Kahneman asks in his book, “We easily think associatively, wee think metaphorically, we think causally, but statistics requires thinking about many things at once, which is something that System 1 is not designed to do.”

 

System 1 operates quickly and cheaply. It takes less energy and effort to run on System 1, but because it is subject to bias and because it makes judgments on incomplete information, it is not reliable for important decisions and calculations based on nuance. We have to engage System 2 to be great at thinking statistically, but statistical thinking still trips up System 2 because it is hard to think about multiple competing outcomes at the same time and weight them appropriately. In Risk Savvy, Gerd Gigerenzer shows that statistical thinking can be substantially improved and that we really can think statistically, but that we need some help from visual aids and tools so that our minds can grasp statistical concepts better. We have to help System 1 so that it can set up System 2 for success if we want to be good at thinking statistically.

 

From the framework that Kahneman lays out, a quick reacting System 1 running on power save mode with limited informational processing power and System 2 operating on incomplete information aggregated by System 1, statistical thinking is nearly impossible. System 1 can’t bring in enough information for System 2 to analyze appropriately. As a result, we fall back on biases or maybe substitute an easier question over the challenging statistical question. Gigerenzer argues that we can think statistically, but that we need the appropriate framing and cues for System 1, so that System 2 can understand the number crunching and leg work that is needed. In the end, statistical thinking doesn’t happen quickly, and requires an ability to hold competing and conflicting information in the mind at the same time, making it hard for us to think statistically rather than anecdotally or metaphorically.

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