What are the assumptions of a classical regression model?

The classical regression model is a statistical method that is used to model the relationship between a dependent variable and one or more independent variables. The classical regression model is based on several key assumptions that must be met in order for the model to be considered valid and reliable. The following are the key assumptions of a classical regression model:

1. Linearity: The relationship between the dependent and independent variables is linear. This means that as the independent variables change, the dependent variable changes in a straight-line relationship. If the relationship between the variables _________ ______ ________ _________ __________ _____ ______ ______ _________ _______.
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