3 answers
(click or scroll down)
One example of a model is the linear regression model. In this model, we aim to fit a straight line to a given set of data points in order to understand the relationship between a dependent variable and one or more independent variables.
For instance, let's consider a study that wants to predict the price of houses based on their size. We collect data on the size of various houses and their corresponding prices. We can use a linear regression model to fit a line that best represents the relationship between the house size (independent variable) and the house price (dependent variable).
The linear regression model will estimate the slope and intercept of the line that minimizes the distance between the predicted house prices and the actual house prices in the data set. Once the model is trained, we can use it to predict the price of new houses based on their size.