In simple linear regression, suppose that the best fit line $y \sim \beta_0 + \beta_1 x$ is obtained. Are $\beta_0$ and $\beta_1$ independent?
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First, make sure you understand the concepts of linear regression, especially how the coefficients eta_0 (intercept) and eta_1 (slope) are calculated. Consider the geometric interpretation of these coefficients in the context of a scatter plot and how changes in one might affect the other. Also, review the underlying assumptions of linear regression and the mathematical relationship between the two coefficients.
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