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Develop a multiple regression model in which market value is taken as Y, house age as X1 and square feet as X2. (1.1) The regression
Develop a multiple regression model in which "market value" is taken as Y, "house age" as X1 and "square feet" as X2. (1.1) The regression equation is (in terms of Y and X 's): (1.2) Value of R2 is (1.3) Value of significance F is Can we say Y is related to X 's in this case? a. Yes b. No (1.4) Use the regression equation to predict the market value of a house that is 30 years old and has 1,800 square feet. Your answer (show your calculations): (1.5) Use the regression equation to predict the market value of a house that is 5 years old and has 2,800 square feet. Your answer (show your calculations): (1.6) p-value for X1 (house age) is Is X1 statistically significant in this model? a. Yes b. No (1.7) p-value for X2 (square feet) is Is X2 statistically significant in this model? a. Yes b. No \begin{tabular}{|r|r|r|} \hline Home Market Value & \\ \hline & & \\ \hline House Age & Square Feet & \\ \hline \hline 33 & 1,812 & $90,000.00 \\ \hline 32 & 1,914 & $104,400.00 \\ \hline 32 & 1,842 & $93,300.00 \\ \hline 33 & 1,812 & $91,000.00 \\ \hline 32 & 1,836 & $101,900.00 \\ \hline 33 & 2,028 & $108,500.00 \\ \hline 32 & 1,732 & $87,600.00 \\ \hline 33 & 1,850 & $96,000.00 \\ \hline 32 & 1,791 & $89,200.00 \\ \hline 33 & 1,666 & $88,400.00 \\ \hline 32 & 1,852 & $100,800.00 \\ \hline 32 & 1,620 & $96,700.00 \\ \hline 32 & 1,692 & $87,500.00 \\ \hline 32 & 2,372 & $114,000.00 \\ \hline 32 & 2,372 & $113,200.00 \\ \hline 33 & 1,666 & $87,500.00 \\ \hline 32 & 2,123 & $116,100.00 \\ \hline 32 & 1,620 & $94,700.00 \\ \hline 32 & 1,731 & $86,400.00 \\ \hline 32 & 1,666 & $87,100.00 \\ \hline 28 & 1,520 & $83,400.00 \\ \hline 27 & 1,484 & $79,800.00 \\ \hline 28 & 1,588 & $81,500.00 \\ \hline 28 & 1,598 & $87,100.00 \\ \hline 28 & 1,484 & $82,600.00 \\ \hline 28 & 1,484 & $78,800.00 \\ \hline 28 & 1,520 & $87,600.00 \\ \hline 27 & 1,701 & $94,200.00 \\ \hline 28 & 1,484 & $82,000.00 \\ \hline 28 & 1,468 & $88,100.00 \\ \hline 28 & 1,520 & $88,100.00 \\ \hline 27 & 1,520 & $88,600.00 \\ \hline 27 & 1,484 & $76,600.00 \\ \hline 28 & 1,520 & $84,400.00 \\ \hline 27 & 1,668 & $90,900.00 \\ \hline 28 & 1,588 & $81,000.00 \\ \hline 28 & 1,784 & $91,300.00 \\ \hline 27 & 1,484 & $81,300.00 \\ \hline 27 & 1,520 & $100,700,00 \\ \hline 27 & 1,520 & $87,200,00 \\ \hline 27 & 1,684 & $96,700.00 \\ \hline 1,581 & $120,700.00 \\ \hline \end{tabular}
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