A Multiple Regression Analysis Produced the Following Tables For X₁= 10, the Predicted Value of Y Is ____________

question 20

Multiple Choice

A multiple regression analysis produced the following tables. $$\begin{array} { | c | c | c | c | c | } \hline & \text { Coefficients } & \text { Stardard Error } & t \text { Statistic } & p \text {-value } \\\hline \text { Irtercept } & 1411.876 & 762.1533 & 1.852483 & 0.074919 \\\hline \boldsymbol { x } _ { 1 } & 35.18215 & 96.8433 & 0.363289 & 0.719218 \\\hline \boldsymbol { x } _ { 1 } { } ^ { 2 } & 7.721648 & \mathbf { 3 . 0 0 7 9 4 3 } & 2.567086 & 0.016115\\\hline\end{array}$$ $$\begin{array} { | c | c | c | c | c | } \hline & \mathrm { df } & \mathrm { SS } & \mathrm { MS } & F \\\hline \text { Regression } & 2 & 58567032 & 29283516 & 57.34861 \\\hline \text { Residual } & 25 & 12765573 & 510622.9 & \\\hline \text { Total } & 27 & 71332605 & & \\\hline\end{array}$$ For x₁= 10, the predicted value of y is ____________.

• A)8.88.
• B)2,031.38
• C)2,53.86
• D)262.19
• E)2,535.86

---

Definitions:

SSE

The sum of squared errors between observed and predicted values in statistical models, indicating the model's accuracy.

SST

Total Sum of Squares, a measure of the total variation in a dataset.

Coefficient Of Determination

A metric used in statistical analysis that assesses how well a model explains and predicts future outcomes, typically squared correlation between observed and predicted values.

SST

Sum of Squares Total, a measure in statistical analysis representing the total variation within a dataset.