Explanation

The F-statistic in a multiple linear regression is calculated as:

$F = \frac{MSR}{MSE}$

Where:

• MSR = Mean Square Regression = 19.234
• MSE = Mean Square Error = 1.358

$F = \frac{19.234}{1.358} = 14.16$

Therefore, the test statistic of the general linear F-test is closest to 14.16.

Key Points:

• The F-test assesses the overall significance of the regression model
• MSR measures the explained variation in the dependent variable
• MSE measures the unexplained variation (error)
• A higher F-statistic indicates stronger evidence against the null hypothesis that all regression coefficients are zero