The chairman of the marketing department at a large state university undertakes a study to relate starting salary (y) after graduation for marketing majors to grade point average (GPA) in major courses. To do this, records of seven recent marketing graduates are randomly selected, and the data shown below on the left are obtained. The MINITAB output obtained by fitting a least squares regression line to the data is below on the right.

a. Find the least squares point estimates b0 and b1 on the computer output and report their values. Interpret b0 and b1. Does the interpretation of b0 make practical sense?
b. Use the least squares line to compute a point estimate of the mean starting salary for all marketing graduates having a grade point average of 3.25 and a point prediction of the starting salary for an individual marketing graduate having a grade point average of 3.25.

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Starting Salary y (Thousands Marketing Graduate GPA, x of Dollars) 3.26 33.8 2.60 29.8 3.35 33.5 2.86 30.4 3.82 36.4 2.21 27.6 347 35.3 Fitted Line Plot StartSal 14.825.707 GPA 36 34 E 32 n 30 28 2.5 3.0 3.5 4.0 2.0 GPA