Use the accompanying set of dependent and independent variables to complete parts a through c below. Click the icon to view the data set. a) Using technology, construct a multiple regression model with the given data. $\hat{y} = \square + \square x_1 + \square x_2$ (Round to three decimal places as needed.) Set of dependent and independent variables \begin{tabular}{|c|c|c|c|c|c|c|c|c|c|} \hline y & 46 & 42 & 39 & 39 & 31 & 25 & 22 & 17 & 10 \\ \hline $x_1$ & 75 & 63 & 77 & 52 & 45 & 47 & 35 & 18 & 15 \\ \hline $x_2$ & 23 & 29 & 19 & 16 & 12 & 17 & 7 & 16 & 10 \\ \hline \end{tabular}
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Use the accompanying set of dependent and independent variables to complete parts a through c below. Click the icon to view the data set. a) Using technology, construct a multiple regression model with the given data. y = ( ) + ( )x1 + ( )x2 (Round to three decimal places as needed.) Set of dependent and independent variables y 10 11 15 15 20 23 27 32 x1 1 4 4 9 7 11 17 20 x2 16 11 13 11 2 9 6 4
Sri K.
Consider the following data for a dependent variable y and two independent variables, x1 and x2. x1 x2 y 30 12 93 47 10 108 25 17 112 51 16 178 40 5 94 51 19 175 74 7 170 36 12 117 59 13 142 76 16 211 The estimated regression equation for these data is ŷ = -18.89 + 2.02x1 + 4.74x2. Here, SST = 15,276.0, SSR = 14,134.9, sb1 = 0.2482, and sb2 = 0.9528. a) Test for a significant relationship among x1, x2, and y. Use alpha = 0.05. Find the value of the test statistic (round your answer to two decimal places). Find the P-value (round your answer to three decimal places). b) Is β1 significant? Use α = 0.05. Find the value of the test statistic (round your answer to two decimal places). Find the p-value (round your answer to three decimal places). c) Is β2 significant? Use α = 0.05. Find the value of the test statistic (round your answer to two decimal places). Find the p-value (round your answer to three decimal places).
Madhur L.
Data for two variables, $x$ and $y,$ follow. $$\begin{array}{c|ccccc}\boldsymbol{x}_{i} & 22 & 24 & 26 & 28 & 40 \\\hline \boldsymbol{y}_{i} & 12 & 21 & 31 & 35 & 70\end{array}$$ a. Develop the estimated regression equation for these data. b. Compute the standardized residuals for these data. Can any of these observations be classified as an outlier? Explain. c. Develop a standardized residual plot against $\hat{y}$. Does the residual plot support the assumptions about $\epsilon$ ? Explain.
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