Parameter estimation

Okay kiddo, let me explain parameter estimation to you. Imagine you are playing a guessing game with your friends, and your friend is thinking of a number in their head but won't tell you what it is. Your goal is to figure out what that number is by asking a bunch of questions.

Now, imagine this number is actually a set of important data that we want to know so we can learn something new. In order to find these data, we use parameter estimation.

Parameter estimation is a fancy way of saying we want to figure out a bunch of important information about something, like the number your friend was thinking of. To do that, we ask a bunch of questions, gather data, and use that data to make an educated guess about what we want to know.

Think of it like baking a cake. We want the cake to taste a certain way, so we need to follow a recipe that tells us how much of each ingredient to use. In parameter estimation, instead of using a recipe, we're using data to find out the important numbers we need to figure out.

For example, let's say we want to know how much rain falls in your city each year. We would gather data about the amount of rain that has fallen in the past, and use that data to make an educated guess about how much rain we might expect in the future. This is parameter estimation.

Overall, parameter estimation is a way to gather information and make educated guesses using the data we have available. Whether we want to know how much rain falls in a city, or what number your friend was thinking of in the guessing game, parameter estimation helps us find the answers we're looking for.