Ononot — In a simple linear regression Y = \beta0 + \beta1 X + \epsil

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Linear Modelinghard

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In a simple linear regression $Y = \beta_0 + \beta_1 X + \epsilon$ , if the variance of the residuals is not constant, $Var(\epsilon|X) = \sigma^2 X^2$ , which statement is true regarding the Ordinary Least Squares (OLS) estimator $\hat{\beta}_1$ ?