You are given the following pairs of observations on (x, Yi), i = 1, ..., 4:...

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You are given the following pairs of observations on (xį, Yi), i = 1, ..., 4: where i = 1, ..., 4. Consider two linear regression models [M1] and [M2] given by μ + Wi [M1] a + Bxi + Ui [M2] Yi = Xi 1 Yi 1 Yi = 2 3 4 3 (a) Compute the OLS estimate for μ, (ie. û), in the linear regression model [M1]. (b) Compute the OLS estimates for a and ß, (ie. â and 3), in the linear regression model [M2]. Interpret these coefficient estimates. (c) Compute the estimate for the regression error variance in model [M2] (i.e. o² = EU²). (d) Test the following hypothesis on the parameters in [M2]. versus H₁ B 0.100 at a = 0.1. Ho = 0.100 : You are given the following pairs of observations on (xį, Yi), i = 1, ..., 4: where i = 1, ..., 4. Consider two linear regression models [M1] and [M2] given by μ + Wi [M1] a + Bxi + Ui [M2] Yi = Xi 1 Yi 1 Yi = 2 3 4 3 (a) Compute the OLS estimate for μ, (ie. û), in the linear regression model [M1]. (b) Compute the OLS estimates for a and ß, (ie. â and 3), in the linear regression model [M2]. Interpret these coefficient estimates. (c) Compute the estimate for the regression error variance in model [M2] (i.e. o² = EU²). (d) Test the following hypothesis on the parameters in [M2]. versus H₁ B 0.100 at a = 0.1. Ho = 0.100 :

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A To compute the OLS estimate for 4 in the linear regression model we need to estimate the intercept and slope parameters in the model y x u where u i... View the full answer