In a multiple linear regression analysis, statistical model utility is determined by the value of R2 and 2s, while practical model utility is determined by the Global F-test p-value.
a) true
b) false

In a multiple linear regression analysis, the statistical model utility is determined by the value of R2 and ∂2, while the Global F test p-value determines the practical model.

This statement is true because if F statistics is significant, then the entire multiple regression model is useful for the prediction of y.

The F test is a statistical test that is very flexible. F test can evaluate multiple model terms.

The F test indicates whether a linear regression model provides a better fit to data than a model that contains no independent variable.

The F test for overall significance has two hypotheses:

1- Null hypothesis:

The fit of the intercept only model and your model are equal.

2- Alternative hypothesis:

The fit of the intercept-only model is significantly reduced compared to your model.

Compare p-value for the F test,

If the p-value is less than the significance level, the sample data provide sufficient evidence that the regression model fits the data better with no independent variable.

In a multiple linear regression analysis, statistical model utility is determined by the value of R2 and 2s, while practical model utility is determined by the Global F-test p-value. a) true b) false

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In a multiple linear regression analysis, statistical model utility is determined by the value of R2 and 2s, while practical model utility is determined by the Global F-test p-value.
a) true
b) false