Prediction of the mean value of the dependent variable y for values of the independent variables x₁, x₂, . . . , x_q that are outside the experimental range is called A)dummy variable. B)overfitting. C)extrapolation. D)interaction.

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Extrapolation refers to predicting the value of the dependent variable for values of the independent variables that are beyond the range of the data that was used to develop the model. It should be avoided as it may lead to unreliable predictions. Dummy variable refers to a binary variable that represents the presence or absence of a particular characteristic or attribute. Overfitting refers to a model that is too complex and fits the noise in the data rather than the underlying pattern. Interaction refers to the effect of one independent variable on the relationship between another independent variable and the dependent variable.

Prediction of the Mean Value of the Dependent Variable Y