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Exhibit 12-9
a Regression and Correlation Analysis Resulted in the Following

question 78

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Exhibit 12-9
A regression and correlation analysis resulted in the following information regarding a dependent variable y) and an independent variable x) .
ΣX=90ΣYYˉ) XXˉ) =466ΣY=170ΣYY) 2=1434n=10SSE=505.98ΣXXˉ) 2=234\begin{array}{ll}\Sigma \mathrm{X}=90 & \Sigma \mathrm{Y}-{\bar{\mathrm{Y}}) X}-\bar{X}) =466 \\\Sigma \mathrm{Y}=170 & \Sigma \mathrm{Y}-\overline{\mathrm{Y}}) ^{2}=1434 \\\mathrm{n}=10\\\mathrm{SSE}=505.98 & \Sigma \mathrm{X}-\bar{X}) ^{2}=234 \end{array}

-Refer to Exhibit 12-9. The sum of squares due to regression SSR) is

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Definitions:

Marginal Revenue Product Curve

A graphical representation showing the additional revenue generated by employing one more unit of a resource.

Marginal Revenue Product

The additional revenue generated from employing one more unit of a resource, assuming all else constant.

Labor Supply Curves

Graphical representations showing the relationship between the wages offered by employers and the amount of labor workers are willing to supply at those wages.

Marginal Revenue Product

The extra income obtained by utilizing an additional unit of a resource.

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