How does the least squares method work in the context of simple linear regression?
- It maximizes the sum of the residuals
- It maximizes the sum of the squared residuals
- It minimizes the sum of the residuals
- It minimizes the sum of the squared residuals
In the context of simple linear regression, the least squares method works by minimizing the sum of the squared residuals (the differences between the observed and predicted values). This approach ensures that the regression line is the best fit to the data.
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