Mathematics, 06.05.2020 03:22, jumeljean123oythxy
The following estimated regression equation was developed for a model involving two independent variables.
y hat = 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.
y hat = 42.0 + 9.01x1
a. In the two independent variable case, the coefficient x1 represents the expected change in - Select your answer -yx1x2Item 1corresponding to a one unit increase in - Select your answer -yx1x2Item 2 when - Select your answer -yx1x2Item 3 is held constant.
In the single independent variable case, the coefficient x1 represents the expected change in - Select your answer -yx1x2Item 4corresponding to a one unit increase in - Select your answer -yx1x2Item 5 .
b. Could multicollinearity explain why the coefficient of x1 differs in the two models? Assume that x1 and x2 are correlated.
- Select your answer -Yes, because a change in x1 would be accompanied by a change in x2Yes, because a change in x1 would not be accompanied by a change in x2
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The following estimated regression equation was developed for a model involving two independent vari...
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