The dean of the Business School at a small Florida college wishes to determine whether theâ grade-point averageâ (GPA) of a graduating student can be used to predict theâ graduate's starting salary. Moreâ specifically, the dean wants to know whether higher GPAs lead to higher starting salaries. Records for 23 of lastâyear's Business School graduates are selected atâ random, and data on GPAâ (x) and starting salaryâ (y, inâ $thousands) for each graduate were used to fit the modelâE(y)equals=beta 0β0plus+beta 1β1x. The results of the simple linear regression are provided below. Suppose aâ 95% prediction interval for y when x=3.00 isâ (16,21). Interpret the interval. y=4.25plus+â2.75x, SSxy=â5.15, SSxx=â1.87, SSyy=â15.17, SSE=1.0075Range of theâ x-values:ââ2.23â3.85Range of theâ y-values:ââ9.3â15.6A. We areâ 95% confident that the starting salary of a Business School graduate will increase betweenâ $16,000 andâ $21,000 for everyâ 3-point increase in GPA. B. We areâ 95% confident that the starting salary of a Business School graduate with a GPA of 3.00 will fall betweenâ $16,000 andâ$21,000.C. We areâ 95% confident that the mean starting salary of all Business School graduates with GPAs of 3.00 will fall betweenâ$16,000 andâ $21,000.D. We areâ 95% confident that the starting salary of a Business School graduate will fall betweenâ $16,000 andâ $21,000.