Ononot — In a simple linear regression Yi = \beta0 + \beta1 Xi + \eps

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Linear Modelinghard

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In a simple linear regression $Y_i = \beta_0 + \beta_1 X_i + \epsilon_i$ , suppose you scale the predictor by a factor $k > 0$ , such that $X_i^* = kX_i$ . How does the new least-squares slope estimator $\hat{\beta}_1^*$ compare to the original slope estimator $\hat{\beta}_1$ ?