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A Multiple Linear Regression Analysis Involving 45 Observations Resulted in the Following

Question 47

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A multiple linear regression analysis involving 45 observations resulted in the following least squares prediction equation: y^=.408+1.3387x1+2.1x2\hat { y } = .408 + 1.3387 x _ { 1 } + 2.1 x _ { 2 } .
The SSE for the above model is 49.
Addition of two other independent variables to the model,resulted in the following multiple linear regression equation: y^=1.2+3x1+12x2+4x3+8x4\hat { y } = 1.2 + 3 x _ { 1 } + 12 x _ { 2 } + 4 x _ { 3 } + 8 x _ { 4 } .
The latter model's SSE is 40.
-Determine the degrees of freedom regression (explained variation),degrees of freedom error (unexplained variation),and total degrees of freedom for the latter model (the model with four independent variables).

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dfR = 4,df...

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