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A Regression and Correlation Analysis Resulted in the Following Information

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A regression and correlation analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x) . Σx=90(yyx) (xx) =466Σy=170(x) 2=234n=10Σ(yy2) 2=1434SSE=505.98\begin{array} { l l } \Sigma x = 90 & \sum \left( y - \frac { y } { x } \right) \left( x - { } ^ { x } \right) = 466 \\\Sigma y = 170 & \sum ( x - ) ^ { 2 } = 234 \\n = 10 & \Sigma \left( y - y ^ { 2 } \right) ^ { 2 } = 1434 \\\mathrm { SSE } = 505.98 &\end{array} The sum of squares due to regression (SSR) is


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