Скачать или смотреть The following estimated regression equation was developed for a model involving two independent var…

The following estimated regression equation was developed for a model involving two independent variables. Å· = 40.7 + 8.63x1 + 2.71x2 After x2 was dropped from the model, the least squares method was used to obtain an estimated regression equation involving only x1 as an independent variable. Å· = 42.0 + 9.01x1 (a) Give an interpretation of the coefficient of x1 in both models. In the two independent variable case, the coefficient of x1 represents the expected change in y corresponding to a one unit increase or decrease in x1 when x2 is held constant. In the single independent variable case, the coefficient of x1 represents the expected change in y corresponding to a one unit increase in x1. (b) Could multicollinearity explain why the coefficient of x1 differs in the two models? If so, how? No. If x1 and x2 are correlated, one would expect a change in x1 to be independent of accompanied by a change in x2.

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