Regression model

Imagine you are playing a game where you have to guess how tall a person will be based on how much they eat every day. You know that the more they eat, the taller they will be. This is called a "relationship" or "association" between two things.

Now let's say you have a lot of data about different people's heights and how much they eat, and you want to use this data to make a "formula" that will help you make better guesses in the future. This is what a regression model does.

First, the model looks at all the data and tries to find the "trend" or "pattern" in the relationship between eating and height. It does this by drawing a straight line that goes through the middle of all the data points. This line is called the "regression line".

Next, the model uses the regression line to make predictions. You can give the model some information about how much a person eats, and it will use the regression line to predict how tall they will be based on the trend in the data.

Overall, a regression model helps you understand how two things are related, and use that information to make predictions about future data.