Explanation
The correct answer is B because the estimated regression equation matches the calculated parameters from the given data.
Step-by-Step Calculation:
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Calculate Covariance between Y and X₁:
Cov(Y,X1)=n−11∑i=1n(X1−Xˉ1)(Y−Yˉ)
From the table, the total sum is 2.759533
Cov(Y,X1)=6−11×2.759533=0.5519
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Calculate Variance of X₁:
Var(X1)=n−11∑i=1n(X1−Xˉ1)2=0.9797
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Calculate Slope Coefficient (β₁):
β^1=Var(X1)Cov(Y,X1)=0.97970.5519=0.5633
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Calculate Intercept (α):
α^=Yˉ−β^1Xˉ1
α^=−0.82833−(0.5633×0.446667)=−1.0799
Therefore, the estimated regression equation is:
Y^=−1.0799+0.5633X1
This matches option B exactly._