In a regression model involving 44 observations, the following estimated regression equation was obtained: ŷ= 10 - 4x12x2 + 8x3 + 8x4 For this model, SSR = 500 and SSE = 3500. Refer to Exhibit 15-33. The coefficient of determination for the above model is approximately -.875 .144 .125 .875

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**Exhibit 15-33**

In a regression model involving 44 observations, the following estimated regression equation was obtained:

\[
\hat{y} = 10 - 4x_1 - 2x_2 + 8x_3 + 8x_4
\]

For this model, SSR (Sum of Squares for Regression) = 500 and SSE (Sum of Squares for Error) = 3500.

Refer to Exhibit 15-33. The coefficient of determination for the above model is approximately ______.

- ○ –.875
- ○ .144
- ● .125
- ○ .875

*Note:* The coefficient of determination (R²) is calculated using the formula:

\[
R^2 = \frac{SSR}{SSR + SSE}
\]
Transcribed Image Text:**Exhibit 15-33** In a regression model involving 44 observations, the following estimated regression equation was obtained: \[ \hat{y} = 10 - 4x_1 - 2x_2 + 8x_3 + 8x_4 \] For this model, SSR (Sum of Squares for Regression) = 500 and SSE (Sum of Squares for Error) = 3500. Refer to Exhibit 15-33. The coefficient of determination for the above model is approximately ______. - ○ –.875 - ○ .144 - ● .125 - ○ .875 *Note:* The coefficient of determination (R²) is calculated using the formula: \[ R^2 = \frac{SSR}{SSR + SSE} \]
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