How to understand randomness

“Chance is a more fundamental conception than causality”—Max Born, Nobel Laureate.


The Xs and Os above represent the results of 200 coin tosses. X is tails and O is heads. You can probably find patterns in this data. For instance the run of six Xs near the end of the string. But this is a random series of heads and tails. Such randomness should be expected in 200 random tosses.

If this sequence represented the daily movement in the price of Bitcoin people would believe an expert who could explain why it’s so volatile. If the Xs and Os were your boss’s success or failure at coming up with new product ideas, you’d probably see all the reasons for their genius (or not).

The problem with randomness is that it's everywhere but our minds are ill-equipped to deal with it. We think every effect has a cause and we see patterns in randomness. It’s very hard not to do this. When things are complex, it’s vital to know what tools are at your disposal to help you distinguish between random noise and meaningful signals.

“The theory of randomness is fundamentally a codification of common sense,” writes Leodard Mlodinow in The Drunkard’s Walk. Yet, it’s subtle. To understand randomness—to distinguish the meaningful patterns amongst all the patterns of nature and the ones we make—takes experience and methodical reasoning. Intuition is an extremely poor guide when it comes to probability.

A basic working knowledge of probability and statistics is table stakes in the digital age. Complex problems can be exceptionally wicked. The math tools used in finance, science, and technology are well beyond most people. That makes it even more important to be fluent in a few key ideas from statistics.

The more random things seem to be, the more we want to be in control. And the more we feel the need to be in control, the less accurate our perception of random events will be. Many experiments have been conducted that show that people will “play lip service to the concept of chance,” but “behave as though chance events are subject to control.”

It’s even worse in real life because randomness is far less obvious. We are more invested in outcomes and motivated to influence them. It’s hard to resist the illusion of cause and effect when it’s bound up in an illusion of control. Therefore, a basic understanding of statistical tools is vital. You want to know that your actions are solving the problem.