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In the Regression Model Yi=β0+β1Xi+β2Di+β3(Xi×Di)+uiY _ { i } = \beta _ { 0 } + \beta _ { 1 } X _ { i } + \beta _ { 2 } D _ { i } + \beta _ { 3 } \left( X _ { i } \times D _ { i } \right) + u _ { i }

Question 2

Multiple Choice

In the regression model Yi=β0+β1Xi+β2Di+β3(Xi×Di) +uiY _ { i } = \beta _ { 0 } + \beta _ { 1 } X _ { i } + \beta _ { 2 } D _ { i } + \beta _ { 3 } \left( X _ { i } \times D _ { i } \right) + u _ { i } where X is a continuous variable and D is a binary variable, β3\beta _ { 3 }


A) indicates the slope of the regression when D=1 .
B) has a standard error that is not normally distributed even in large samples since D is not a normally distributed variable.
C) indicates the difference in the slopes of the two regressions.
D) has no meaning since (Xi×Di) =0 when Di=0\left( X _ { i } \times D _ { i } \right) = 0 \text { when } D _ { i } = 0 \text {. }

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