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true or false: linearity is justified if the residuals are randomly dispersed across the values of a predictor variable.

User Norbitrial
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Answer: False

Step-by-step explanation: False. Linearity is a property of a mathematical model or equation, not of the residuals of that model. In general, the residuals of a model should be randomly dispersed across the values of a predictor variable if the model is a good fit for the data, but this is not a justification for linearity. Linearity refers to the relationship between the predictor and response variables in a model, and whether that relationship can be adequately represented by a straight line.

User Joe Germuska
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