Using the data provided, find the Sum of Squared Error (SSE) for the model $\hat{y} = 0.6x + 8.9$ X y $\hat{y}$ y-$\hat{y}$ ($y-\hat{y}$)² 0 5 7 8.5 12 11 19 14.5 SSE= (round to 2 decimal places as needed) A. $\hat{y} = 0.6x+8.9$ is the best possible linear model for the data because the SSE is small B. $\hat{y} = 0.6x+8.9$ is the best possible linear model for the dat because the SSE is large C. The lone SSE cannot determine if the model is the best for the given set of data
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6x + 8.9\). For \(x = 0\): \[ \hat{y} = 0.6(0) + 8.9 = 8.9 \] For \(x = 7\): \[ \hat{y} = 0.6(7) + 8.9 = 4.2 + 8.9 = 13.1 \] For \(x = 12\): \[ \hat{y} = 0.6(12) + 8.9 = 7.2 + 8.9 = 16.1 \] For \(x = 19\): \[ \hat{y} = 0.6(19) + 8.9 = 11.4 + 8.9 = 20.3 \] Show more…
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