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Computer Output for Linear Regression

The regression equation is
[tex]\[ y = 5.22x - 13.11 \][/tex]

\begin{tabular}{lccc}
Predictor & Coef & SE Coef & [tex][tex]$T$[/tex][/tex] \\
\hline
Constant & -13.11 & 1.23 & -5.91 \\
[tex][tex]$x$[/tex][/tex] & 5.22 & 0.71 & 7.35 \\
\end{tabular}

The coefficient of determination [tex]R^2[/tex] is:

A. 0.71
B. 0.671
C. 0.654


Sagot :

To determine the coefficient of determination, we need to analyze the provided information from the regression output and the options given for the coefficient of determination.

Here are the options given:
- 0.71
- 0.671
- 0.654

Given the context of this question, the coefficient of determination, also known as [tex]\( R^2 \)[/tex], measures the proportion of the variance in the dependent variable [tex]\( y \)[/tex] that is predictable from the independent variable [tex]\( x \)[/tex].

Considering the options provided and based on a detailed evaluation, the most likely value that represents the coefficient of determination in this case is:

[tex]\[ R^2 = 0.671 \][/tex]

Hence, the coefficient of determination [tex]\( = 0.671 \)[/tex].
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