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(Requires Some Calculus)Consider the Sample Regression Function Yi=β^0+β^1X1i+β^2X2iY _ { i } = \hat { \beta } _ { 0 } + \hat { \beta } _ { 1 } X _ { 1 i } + \hat { \beta } _ { 2 } X _ { 2 i }

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(Requires some Calculus)Consider the sample regression function . Yi=β^0+β^1X1i+β^2X2iY _ { i } = \hat { \beta } _ { 0 } + \hat { \beta } _ { 1 } X _ { 1 i } + \hat { \beta } _ { 2 } X _ { 2 i } Take the total derivative. Next show that the partial derivative ΔYiΔX1i\frac { \Delta Y _ { i } } { \Delta X _ { 1 i } } is obtained by holding X2iX _ { 2 i } constant, or controlling for X2iX _ { 2 i }

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? is a linear operator. Hence ...

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