Approximate Bayesian computation

Okay kiddo, let me explain approximate Bayesian computation (ABC) to you in a way you can understand.

Let's say you want to know how likely it is for you to get a toy from a surprise bag. There are many different toys in the bag, so it's hard to know exactly which one you'll get, but you can make a guess based on what you already know.

Similarly, scientists use Bayesian methods to make educated guesses about things they want to study, like how a certain gene affects a person's chances of getting a certain disease. However, sometimes it's hard to get all the data they need to make accurate guesses, so they use ABC to get a close approximation.

ABC works by creating many simulations of the process being studied and comparing them to the real-life data they have. They adjust the parameters of the simulations until they closely match the data, and then use those simulations to make their guesses.

So, just like you might make an educated guess about which toy you'll get based on the ones you already have, scientists use ABC to make educated guesses about things they want to study based on the data they have. It's not always perfect, but it helps get us closer to the answers we need.