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What are the assumptions of linear regression?  

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  1. Linearity: The relationship between the dependent and independent variables is linear.
  2. Independence: Observations are independent of each other.
  3. Homoscedasticity: The variance of residuals is constant across all levels of the independent variable.
  4. Normality: Residuals are normally distributed.

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