Each year a nationally recognized publication conducts its 'Survey of America's Best Graduate and Professional Schools.' An academic advisor wants to predict the typical starting salary of a graduate at a top business school using GMAT score of the school as a predictor variable. Total GMAT scores range from 200 to 800. A simple linear regression of SALARY versus GMAT using 25 data points yields the regression equation given below. y = 228x - 92,040 Give an interpretation of the y-intercept. The value has no practical interpretation since a GMAT of 0 is nonsensical and outside the range of the sample data. We estimate the base SALARY of graduates of a top business school to be $-92,040. We estimate SALARY to decrease $92,040 for every 1-point increase in GMAT. We expect to predict SALARY to within 2(92040) = $184,080 of its true value using GMAT in a straight-line model.

Respuesta :

Answer:

The correct answer is the value has no practical interpretation since a GMAT of 0 is nonsensical and outside the range of the sample data.

Step-by-step explanation:

Solution

Given that:

We define Define Y : dependent variable ( Starting salary of a graduate at a top business school )

Thus,

X : independent variable ( GMAT score )

So,

The Required linear regression equation is stated below:

y = 228 x - 92,040

Here,

The y intercept is = - 92040

The Interpretation of the y - intercept  is defined as:

The value has no practical interpretation since a GMAT of 0 is nonsensical and outside the range of the sample data .

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