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Linear regression is a statistical method used to model the linear relationship between a dependent variable and one or more independent variables. It is a popular technique for understanding the relationship between different variables and predicting outcomes.

In linear regression, the goal is to fit a line to a set of data points. This line is called the regression line, and it is used to predict the value of the dependent variable based on the values of the independent variables. The process of fitting a line to the data is known as "regression."

One common method for fitting a line to the data is the least squares method. In this method, the line is chosen to minimize the sum of the squared differences between the observed data points and the predicted values. This results in the "best fit" line, which can be used to make predictions about the dependent variable.

Linear regression is a powerful tool that is widely used in many fields, including finance, economics, and engineering. It is a simple and effective way to understand the relationship between different variables and make predictions based on that relationship. If you're interested in learning more about linear regression and how it is used in data analysis, be sure to check out our video on the topic.
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