A multiple regression analysis produced the following tables. $$\begin{array} { | c | c | c | c | c | } \hline & \text { Coefficients } & \text { Stardard Error } & t \text { Statistic } & p \text {-value } \ \hline & & & & \ \hline \text { Irtercept } & 1411.876 & 762.1533 & 1.852483 & 0.074919 \ \hline x _ { 1 } & 35.18215 & 96.8433 & 0.363289 & 0.719218 \ \hline x _ { 1 } { } ^ { 2 } & 7.721648 & 3.007943 & 2.567086 & 0.016115 \ \hline \end{array}$$ $$\begin{array} { | c | c | c | c | c | } \hline & \mathrm { df } & \mathrm { SS } & \mathrm { MS } & F \ \hline \text { Repression } & 2 & 58567032 & 29283516 & 57.34861 \ \hline \text { Residual } & 25 & 12765573 & 5106229 & \ \hline \text { Total } & 27 & 71332605 & & \ \hline \end{array}$$ The regression equation for this analysis is ____________. A) = 762.1533 + 96.8433 x₁ + 3.007943 x₁² B) = 1411.876 + 762.1533 x₁ + 1.852483 x₁² C) = 1411.876 + 35.18215 x₁ + 7.721648 x₁² D) = 762.1533 + 1.852483 x₁ + 0.074919 x₁² E) = 762.1533 - 1.852483 x₁ + 0.074919 x₁²

Question

Quizplus · Accepted Answer

The regression equation is constructed using the coefficients from the regression analysis table. The intercept is 1411.876, the coefficient for $x_1$ is 35.18215, and the coefficient for $x_1^2$ is 7.721648, which matches option C.

A Multiple Regression Analysis Produced the Following Tables The Regression Equation for This Analysis Is ____________