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

question 8

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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=228 s=3213df=23t=6.67\hat { \beta } _ { 0 } = - 92040 \hat { \beta } 1 = 228 \mathrm {~s} = 3213 \mathrm { df } = 23 \quad t = 6.67
Set up the null and alternative hypotheses for testing whether a linear relationship exists between SALARY and GMAT.


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