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An Academic Advisor Wants to Predict the Typical Starting Salary β^0=92040β^1=228s=3213r2=.66r=.81df=23t=6.67\hat { \beta } _ { 0 } = - 92040 \hat { \beta } 1 = 228 s = 3213 r ^ { 2 } = .66 r = .81 \quad \mathrm { df } = 23 \quad t = 6.67

question 55

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An academic advisor wants to predict the typical starting salary of a graduate at a top business school using the GMAT score of the school as a predictor variable. A simple linear regression of
SALARY versus GMAT using 25 data points is shown below. β^0=92040β^1=228s=3213r2=.66r=.81df=23t=6.67\hat { \beta } _ { 0 } = - 92040 \hat { \beta } 1 = 228 s = 3213 r ^ { 2 } = .66 r = .81 \quad \mathrm { df } = 23 \quad t = 6.67
A 95%95 \% prediction interval for SALARY when GMAT =600= 600 is approximately ($37,915,$51,984) ( \$ 37,915 , \$ 51,984 ) . Interpret this interval.


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