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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 :

GinnyAnsweridn
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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