What a Lot of Bull!

Our weekly explainer on economics using lessons from popular culture. In Installment 26, Ferdinand the Bull is a victim of the Law of Small Numbers.

Big companies get a bad rap. but 20th Century Fox deserves praise. They have just come out with a movie that imparts economics education to a whole new generation of youngsters. Ferdinand  is not just great fun to watch, but is also enlightening about the machinery of the human mind. Everyone who sees this film will now understand the Law of Small Numbers.

The film introduces us to Ferdinand, a bull who is quite the opposite of his fellow bulls. If the stereotypical bull is a ferocious beast who headbangs to heavy metal, Ferdinand is a gentle soul who would probably enjoy Mozart. He’s a brave bull, but he doesn’t like fighting — what’s the point? But because of his ginormous size, it is assumed that he must be a heck of a fighter. This is fallacious thinking.

The Law of Small Numbers, which is less a law and more a fallacy to avoid, can be defined as a “judgmental bias which occurs when it is assumed that the characteristics of a sample population can be estimated from a small number of observations or data points.” Put simply, it’s the fallacy you commit when you “generalize from small amounts of data,” as this profile of Daniel Kahneman puts it. (This is one of the biases explored by Kahneman and Amos Tversky, the two pioneers of Behavioral Economics.) This is also now referred to as Hasty Generalization.

Examples of this abound. Maybe we evaluate mutual funds based on their three-year track record, which is too small a sample size. Maybe we have one bad meal at an acclaimed restaurant, and assume, based on that one meal, that the acclaim is all hype. Maybe we get a Whatsapp forward about forcible conversion and assume that all conversions must be forced. Or maybe we look at a big bull, and because we have known big bulls to be ferocious, we assume that Ferdinand is also that sort of beast.

Now, in order to navigate our world, it is useful to generalize. Indeed, such generalization is hardwired into us. For example, if we see a snake under our bed, it would be silly to ponder, What is the sample size from which I draw my conclusion about snakes being dangerous? Most snakes are not poisonous, so would I be judging this one harshly by running away from it? No, if you think like that, you’ll eventually take yourself out of the gene pool.

The world is too complex, and time too scarce, for us to make every judgement with the rigour of a scientist.  But it is important to be aware of the bugs in our brain, and one of them is this instinct towards simplification. We can make better decisions, and live a richer life, if we consider sample sizes before rushing to judgement about anything.

This is why, for example, I believe that before marriage, the prospective partners should live together for a while so that they get a decent sample size of shared experiences. This is why that self-help slogan of Try, Try Again is so wise, for what may seem like a crushing failure to you is a sample size of one, and you should try again. This is why when a new player breaks into the Indian cricket team, you should not judge him based on a just a handful of innings, because hey, randomness.

Ferdinand the bull does find a happy ending in Ferdinand the film, but it’s just a movie, right? Bulls don’t usually end up happy, right? Well, I have a question for you: how many bulls do you actually know?