The regression model Yi = Bo + BX1i + B2X2i + B3X3i + Ui has been...

  

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The regression model Yi = Bo + B₁X1i + B2X2i + B3X3i + Ui has been estimated using Gretl. The output is below. Model 1: OLS, using observations 1-64 const X1 X2 X3 coefficient -0.0548 -0.0424 0.9681 -1.6377 Mean dependent var Sum squared resid R-squared F(3, 60) Log-likelihood std. error 0.2213 0.1251 0.3456 0.1487 t-ratio -0.2475 -0.3390 2.8013 -11.0100 -0.9636 S.D. dependent var 150.86 S.E. of regression 0.69755 Adjusted R-squared 46.126 P-value(F) -118.25 Akaike criterion 253.14 p-value 0.8054 0.7358 0.0068 0.0000 2.8138 1.5857 0.68243 0 244.5 Schwarz criterion Hannan-Quinn 247.9 Create a complete ANOVA table for this regression (including the columns for 'Sum of squares', 'df' and 'Mean square'. In your answer, you should produce the ANOVA table and show all your working. The regression model Yi = Bo + B₁X1i + B2X2i + B3X3i + Ui has been estimated using Gretl. The output is below. Model 1: OLS, using observations 1-64 const X1 X2 X3 coefficient -0.0548 -0.0424 0.9681 -1.6377 Mean dependent var Sum squared resid R-squared F(3, 60) Log-likelihood std. error 0.2213 0.1251 0.3456 0.1487 t-ratio -0.2475 -0.3390 2.8013 -11.0100 -0.9636 S.D. dependent var 150.86 S.E. of regression 0.69755 Adjusted R-squared 46.126 P-value(F) -118.25 Akaike criterion 253.14 p-value 0.8054 0.7358 0.0068 0.0000 2.8138 1.5857 0.68243 0 244.5 Schwarz criterion Hannan-Quinn 247.9 Create a complete ANOVA table for this regression (including the columns for 'Sum of squares', 'df' and 'Mean square'. In your answer, you should produce the ANOVA table and show all your working.

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ANSWER AND EXPLANATION Refer to image to find the complete We have GAANOVA Table Now ... View the full answer