Which method is commonly used to find the best fitting line in simple linear regression?
- K-means clustering
- Neural network
- The method of least squares
- The method of maximum likelihood
The method of least squares is commonly used to find the best fitting line in simple linear regression. It minimizes the sum of the squares of the residuals (the vertical distances between the observed and predicted values).
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