We decide to conduct a multiple regression analysis to predict the attendance at a major league baseball game. We use the size of the stadium as a quantitative independent variable and the type of game as a qualitative variable (with two levels - day game or night game). We hypothesize the following model: $$E ( y ) = \beta _ { 0 } + \beta _ { 1 } x _ { 1 } + \beta _ { 2 } x _ { 2 } + \beta _ { 3 } x _ { 3 }$$
Where $\mathrm { x } _ { 1 } =$ size of the stadium
$\mathrm { x } _ { 2 } = 1$ if a day game, 0 if a night game

A plot of the $y - x _ { 1 }$ relationship would show: :
A) Two parallel curves
B) Two non-parallel curves
C) Two non-parallel lines
D) Two parallel lines

Question

We decide to conduct a multiple regression analysis to predict the attendance at a major league baseball game. We use the size of the stadium as a quantitative independent variable and the type of game as a qualitative variable (with two levels - day game or night game). We hypothesize the following model: $$E ( y ) = \beta _ { 0 } + \beta _ { 1 } x _ { 1 } + \beta _ { 2 } x _ { 2 } + \beta _ { 3 } x _ { 3 }$$
Where $\mathrm { x } _ { 1 } =$ size of the stadium
 $\mathrm { x } _ { 2 } = 1$ if a day game, 0 if a night game

A plot of the $y - x _ { 1 }$ relationship would show: :
A) Two parallel curves
B) Two non-parallel curves
C) Two non-parallel lines
D) Two parallel lines

Quizplus · Accepted Answer

The Answer of We decide to conduct a multiple regression analysis to predict the attendance at a major league baseball game. We use the size of the stadium as a quantitative independent variable and the type of game as a qualitative variable (with two levels - day game or night game). We hypothesize the following model: $$E ( y ) = \beta _ { 0 } + \beta _ { 1 } x _ { 1 } + \beta _ { 2 } x _ { 2 } + \beta _ { 3 } x _ { 3 }$$
Where $\mathrm { x } _ { 1 } =$ size of the stadium
 $\mathrm { x } _ { 2 } = 1$ if a day game, 0 if a night game

A plot of the $y - x _ { 1 }$ relationship would show: :
A) Two parallel curves
B) Two non-parallel curves
C) Two non-parallel lines
D) Two parallel lines

We Decide to Conduct a Multiple Regression Analysis to Predict E(y)=β0+β1x1+β2x2+β3x3E ( y ) = \beta _ { 0 } + \beta _ { 1 } x _ { 1 } + \beta _ { 2 } x _ { 2 } + \beta _ { 3 } x _ { 3 }E(y)=β0​+β1​x1​+β2​x2​+β3​x3​

We Decide to Conduct a Multiple Regression Analysis to Predict $E ( y ) = \beta _ { 0 } + \beta _ { 1 } x _ { 1 } + \beta _ { 2 } x _ { 2 } + \beta _ { 3 } x _ { 3 }$