For the situation above, write the equation of the probabilistic model of interest.
A) GMAT $= \beta _ { 0 } + \beta _ { 1 }$ (SALARY)
B) Salary $= \beta _ { 0 } + \beta _ { 1 } ($ GMAT $) + \epsilon$
C) Salary $= \beta _ { 0 } + \beta _ { 1 } ($ GMAT $)$
D) GMAT $= \beta _ { 0 } + \beta _ { 1 } ($ SALARY $) + \epsilon$

Question

For the situation above, write the equation of the probabilistic model of interest. 
A) GMAT $= \beta _ { 0 } + \beta _ { 1 }$ (SALARY)
B) Salary $= \beta _ { 0 } + \beta _ { 1 } ($ GMAT $) + \epsilon$
C) Salary $= \beta _ { 0 } + \beta _ { 1 } ($ GMAT $)$
D) GMAT $= \beta _ { 0 } + \beta _ { 1 } ($ SALARY $) + \epsilon$

Quizplus · Accepted Answer

The correct equation for a probabilistic model predicting Salary based on GMAT scores includes an error term ($\epsilon$) to account for randomness or unexplained variation, making option B the correct choice.

For the Situation Above, Write the Equation of the Probabilistic =β0+β1= \beta _ { 0 } + \beta _ { 1 }=β0​+β1​

For the Situation Above, Write the Equation of the Probabilistic $= \beta _ { 0 } + \beta _ { 1 }$