For the situation above, give a practical interpretation of $\hat { \beta } _ { 1 } = 228$.
A) We expect to predict SALARY to within $2 ( 228 ) = \$ 456$ of its true value using GMAT in a straight-line model.
B) We estimate GMAT to increase 228 points for every $\$ 1$ increase in SALARY.
C) We estimate SALARY to increase $\$ 228$ for every 1-point increase in GMAT.
D) The value has no practical interpretation since a GMAT of 228 is nonsensical and outside the range of the sample data.

Question

Quizplus · Accepted Answer

The coefficient $\hat { \beta } _ { 1 } = 228$ in a regression model indicates the expected change in the dependent variable (SALARY) for a one-unit increase in the independent variable (GMAT). Therefore, for every 1-point increase in GMAT score, the SALARY is expected to increase by $228.

For the Situation Above, Give a Practical Interpretation Of β^1=228\hat { \beta } _ { 1 } = 228β^​1​=228

For the Situation Above, Give a Practical Interpretation Of $\hat { \beta } _ { 1 } = 228$