Sciency Words: Stochastic

Hello, friends!  Welcome to another episode of Sciency Words, an ongoing series here on Planet Pailly where we take a closer look at the definitions and etymologies of science or science-related terms.  Today on Sciency Words, we’re talking about:

STOCHASTIC

There are no true synonyms, according to American writer Roy Peter Clark.  Sure, two words may mean basically the same thing.  Two words may be so similar in meaning that you could use them interchangeably.  But there will still be some subtle difference between them, some slight shade of connotation that separates them.  The word “stochastic” is almost a synonym for “random.”  Almost.

Definition of stochastic: In statistics, a stochastic process is a process that is best modeled using a random probability distribution.  The process being modeled may, in fact, be random, or it may not.  The important thing is that a stochastic process is a process that scientists have modeled as if it were random.

Etymology of stochastic: The word comes from an ancient Greek word meaning “to aim in the right direction” or “to guess.”

Lots of things in the world are not truly random, but they may as well be.  The weather.  The economy.  Chemical reactions.  Changes in animal populations.  The orbital drifting of asteroids and comets.  Modeling these things in a strictly deterministic way would be mindbogglingly complicated and utterly impractical.  So scientists create stochastic models instead—models that include some random element to represent the super complicated parts that are impractical to model any other way.

These stochastic models are not perfect, but (as the etymology suggests) they aim us in the right direction, and they allow scientists to make pretty good guesses about what might happen with the weather, or the economy, et cetera, et cetera.

WANT TO LEARN MORE?

I try to avoid telling you to just go read Wikipedia, but the article about this on Wikipedia is actually pretty good.  Most of the other sources I looked at (or tried to look at) were super math heavy.  And you know how I feel about math.