In the regression model $Y _ { i } = \beta _ { 0 } + \beta _ { 1 } X _ { i } + \beta _ { 2 } D _ { i } + \beta _ { 3 } \left( X _ { i } \times D _ { i } \right) + u _ { i }$ where X is a continuous variable and D is a binary variable, $\beta _ { 2 }$
A) is the difference in means in Y between the two categories.
B) indicates the difference in the intercepts of the two regressions.
C) is usually positive.
D) indicates the difference in the slopes of the two regressions.

Question

In the regression model $Y _ { i } = \beta _ { 0 } + \beta _ { 1 } X _ { i } + \beta _ { 2 } D _ { i } + \beta _ { 3 } \left( X _ { i } \times D _ { i } \right) + u _ { i }$ where  X  is a continuous variable and  D  is a binary variable, $\beta _ { 2 }$
A) is the difference in means in  Y  between the two categories.
B) indicates the difference in the intercepts of the two regressions.
C) is usually positive.
D) indicates the difference in the slopes of the two regressions.

Quizplus · Accepted Answer

The Answer of In the regression model $Y _ { i } = \beta _ { 0 } + \beta _ { 1 } X _ { i } + \beta _ { 2 } D _ { i } + \beta _ { 3 } \left( X _ { i } \times D _ { i } \right) + u _ { i }$ where  X  is a continuous variable and  D  is a binary variable, $\beta _ { 2 }$
A) is the difference in means in  Y  between the two categories.
B) indicates the difference in the intercepts of the two regressions.
C) is usually positive.
D) indicates the difference in the slopes of the two regressions.

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 }Yi​=β0​+β1​Xi​+β2​Di​+β3​(Xi​×Di​)+ui​

In the Regression Model $Y _ { i } = \beta _ { 0 } + \beta _ { 1 } X _ { i } + \beta _ { 2 } D _ { i } + \beta _ { 3 } \left( X _ { i } \times D _ { i } \right) + u _ { i }$