Regression Analysis

Regression Analysis – Linear Model Assumptions

Linear regression analysis is based on six fundamental assumptions:

The dependent and independent variables show a linear relationship between the slope and the intercept.

The independent variable is not random.

The value of the residual (error) is zero.

The value of the residual (error) is constant across all observations.

The value of the residual (error) is not correlated across all observations.

The residual (error) values follow the normal distribution.

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