In everyday conversation, we use the word “random” to explain a whole host of different situations. We say random when we mean “no discernible pattern.” But on closer inspection, “random” is just some fancy version of “there are too many variables” or even “I dunno.”
Think about it this way. What could be more random than rolling some dice? But in a perfect, virtual world, we could calculate all the physics and variables, and know what the dice would bring.
We know that’s not realistic. In the real world, it’s just a “toss of the dice.”
We can imagine the same thing for predicting weather. We all know the weather’s hard to predict because it’s a whole bunch of variables and half-understood systems all mashing together to produce results. Or, as the guy said about the weather in The Weather Man, “I don’t know. It’s a guess. It’s wind, man. Blows all over the place.”
The Magic Power(s) of Statistics
So, if we live in this complicated world, how do we make sense of it at all? The long answer is careful analysis and the scientific method, of course. The short answer is often previous experience, “gut” instinct, and a fair amount of bravado.
But there’s a stage that falls somewhere in between the two. A basic understanding of the field of statistics helps with the scientific analysis of data (and any other data), but it has two other important advantages.
The first is that it allows us to make clear and rational decisions even with limited data. That’s not because stats makes you a supergenius, but because studying stats gives you new schemas for understanding not just data, but also different types of data.
We make decisions without enough data every day. We “guess.” In many cases, it’s not even that we have to make the best decision, but that making any decision will allow us to progress. After all, in the real world, we’re not wedded to every decision. We can always change our minds later.
The second is that a clear understanding of statistics prevents us from being hoodwinked by massaged data. That’s right! Not only can statistics help us make good decisions, it can also stop us from being fooled into making bad ones.
Once we have some experience with research design, such classics as “seven out of 10 doctors surveyed love this product” means a whole lot less. We begin asking questions like, “how was the sample group selected?” and of course “Which 10 doctors were surveyed?”
In the past, the study of Latin, Greek, and French were necessary for a person to be considered educated. In the information age, a working knowledge of statistics, at least to the point that we know a p-value from a piece of pie, is invaluable.