M6practiceQuizquestions3

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Arizona State University *

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330

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Statistics

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Feb 20, 2024

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docx

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Uploaded by sweetdreamz1014

The accurate statement about multiple linear regression is: "The effect of each individual predictor is tested through an F test." In multiple linear regression, the effect of each individual predictor on the dependent variable is tested through an F-test, specifically the F-statistic associated with each predictor's coefficient. This test assesses whether the predictor contributes significantly to explaining the variance in the dependent variable, after accounting for the other predictors in the model. The other statements are not accurate:  Removing a predictor from a multiple regression model may or may not lower the effect size of the model. The impact of removing a predictor depends on its contribution to the model and its relationship with other predictors.  Using the "Forward" method to build a multiple regression model in SPSS does not guarantee that the resulting model will only contain significant predictors. This method adds predictors to the model one at a time based on their contribution to the model's fit, but it does not necessarily ensure that all predictors in the final model will be significant.  The strength of the Pearson's correlation between a predictor and the outcome variable is typically stronger than that of the semipartial correlation between the same two variables. Pearson's correlation measures the strength and direction of the linear relationship between two variables, whereas the semipartial correlation measures the unique contribution of one variable

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