What are the assumptions of linear regression?

Data Science, AI and ML
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Assumptions of linear regression.

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There are four assumptions associated with a linear regression model:

  • Linearity: The relationship between X and the mean of Y is linear.
  • Homoscedasticity: The variance of residual is the same for any value of X.
  • Independence: Observations are independent of each other.
  • Normality: For any fixed value of X, Y is normally distributed.