$5 of 15 P 9) A study of the top MBA programs attempted to predict the average starting salary in 11000's) of graduates of the program based on the amount of tition (in 810008) charged by the program and the average GMAT score of the program's students. The results of a regression analysis based on sample of 75 MBA program is shown below Least squares Linear Regression at Salary Predictor Variables Coefficient Sto Error T VIF Constant - 203.402 51.6573 -3.94 0.0002 00 Gmat 0.39412 0.09029 436 0.0000 20 Tuition 0.920120.17875 5.15 0.0000 20 The model was then used to create confidence and prediction intervals fory and for ElY) when the tuition charped by the MBA program was 175.000 and the GMAT Roore was 67. The results are shown here 95% confidence interval for E/Y: (1126,610.1136 540) 35% prediction interval for Y: 190,113, 1170.180) Which of the following interpretation is correct if you want to use the model to estimate Y for a single MBA program! A) We are 95% confident that the average starting salary for graduates of a single MBA program that charges 375,000 intuition and has an average GMAT score of 675 will fall between 1126 610 and 1136.640 B) We are 95% confident that the average starting salary for graduates of a single MBA program that charges 175.000 in tuition and has an average GMAT score of 675 will all between 190,113 and 1173.16.30 C) We are confident that the average of all starting salaries for graduates of all MBA programs that charge 175.000 intuition and have an average GMAT score of 675 will fall between 1126,610 and 1136.540 D) We are 96% confident that the average of all starting salaries for graduates at all MBA programs that charge 175,000 in tation and have an average GMAT score of 675 will fall between 190.113 and 1172.16.30 10) 10) During its manufacture a product is subjected to four different tests in sequential order. An efficiency expert claims that the fourth (and last) test is unnecessary to its results can be predicted based on the first three tests. To test this claim. multiple regression will be used to model Teste score, as a function of Test score (1), Test score 1x2), and Test score (x3). Note: All test scores range from 200 to 300, with higher scores indicative of a higher quality product Consider the model En *****8212/99 The first-order model was fit to the data for each of 12 units sampled from the production line A 85prediction interval for Teste score of a product with Textt - 540. Test2 = 750. and Tests - 710 Is (583.799). Interpret this result A We are 95% contident that a product's Test score will fail between 583 and 793 points when the first three scores are 500, 750, and 710 Nespectively B) We are 96% confident that a products Test score increases by an amount between 583 and 799 points for every 1 point increase in Test score, holding Test 2 and Test score constant C) Since is outside the interval, there is evidence of a linear relationship between Test score and any of the other test scores D) We are 95% confident that the mean Test score of all manufactured products talls between 583 and 790 points $5 of 15 P 9) A study of the top MBA programs attempted to predict the average starting salary in 11000's) of graduates of the program based on the amount of tition (in 810008) charged by the program and the average GMAT score of the program's students. The results of a regression analysis based on sample of 75 MBA program is shown below Least squares Linear Regression at Salary Predictor Variables Coefficient Sto Error T VIF Constant - 203.402 51.6573 -3.94 0.0002 00 Gmat 0.39412 0.09029 436 0.0000 20 Tuition 0.920120.17875 5.15 0.0000 20 The model was then used to create confidence and prediction intervals fory and for ElY) when the tuition charped by the MBA program was 175.000 and the GMAT Roore was 67. The results are shown here 95% confidence interval for E/Y: (1126,610.1136 540) 35% prediction interval for Y: 190,113, 1170.180) Which of the following interpretation is correct if you want to use the model to estimate Y for a single MBA program! A) We are 95% confident that the average starting salary for graduates of a single MBA program that charges 375,000 intuition and has an average GMAT score of 675 will fall between 1126 610 and 1136.640 B) We are 95% confident that the average starting salary for graduates of a single MBA program that charges 175.000 in tuition and has an average GMAT score of 675 will all between 190,113 and 1173.16.30 C) We are confident that the average of all starting salaries for graduates of all MBA programs that charge 175.000 intuition and have an average GMAT score of 675 will fall between 1126,610 and 1136.540 D) We are 96% confident that the average of all starting salaries for graduates at all MBA programs that charge 175,000 in tation and have an average GMAT score of 675 will fall between 190.113 and 1172.16.30 10) 10) During its manufacture a product is subjected to four different tests in sequential order. An efficiency expert claims that the fourth (and last) test is unnecessary to its results can be predicted based on the first three tests. To test this claim. multiple regression will be used to model Teste score, as a function of Test score (1), Test score 1x2), and Test score (x3). Note: All test scores range from 200 to 300, with higher scores indicative of a higher quality product Consider the model En *****8212/99 The first-order model was fit to the data for each of 12 units sampled from the production line A 85prediction interval for Teste score of a product with Textt - 540. Test2 = 750. and Tests - 710 Is (583.799). Interpret this result A We are 95% contident that a product's Test score will fail between 583 and 793 points when the first three scores are 500, 750, and 710 Nespectively B) We are 96% confident that a products Test score increases by an amount between 583 and 799 points for every 1 point increase in Test score, holding Test 2 and Test score constant C) Since is outside the interval, there is evidence of a linear relationship between Test score and any of the other test scores D) We are 95% confident that the mean Test score of all manufactured products talls between 583 and 790 points