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Multiple regression procedures may be used when two or more interval-level measures serve as predictors of...

Multiple regression procedures may be used when two or more interval-level measures serve as predictors of some normally distributed interval-level dependent variable. In this model, the regression coefficient for any independent or predictor variable (X­1) represents the change in the dependent or outcome variable (Y) associated with one unit change in X1, while controlling for or maintaining other predictors (X2, X3, etc.) at constant. If you required to use this model in the analysis of the data of a research study, which of the following assumptions is (are) necessary for a valid result?

The dependent variable should be normally distributed around the prediction line

There must be a linear relationship between the dependent variable and the independent variables

Both of the above

None of the above

math   Statistics-And-Probability   
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There must be a linear relationship between the dependent variable and the independent variables

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