The regression method that assumes a linear relationship between the dependent and independent variables is called Linear Regression. This approach models the relationship by fitting a straight line to the data points, minimizing the sum of the squared differences between the observed and predicted values. It is commonly used for predicting outcomes and understanding the strength of relationships between variables.
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