A prospective MBA student would like to examine the factors that impact starting salary upon graduation and decides to d
Posted: Wed May 04, 2022 12:11 pm
reject, do not reject
sufficient, insufficient
A prospective MBA student would like to examine the factors that impact starting salary upon graduation and decides to develop a model that uses program per-year tuition as a predictor of starting salary. Data were collected for 37 full-time MBA programs offered at private universities. The data are stored in the accompanying table. The least-squares regression equation for these data is Y₁ = -14,012.822 +2.428X; and the standard error of the estimate is Syx = 16,131.781. Assume that the straight-line model is appropriate and there are no serious violations the assumptions of the least-squares regression model. Complete parts (a) and (b) below. Click the icon to view the data on program per-year tuition and mean starting salary. a. At the 0.01 level of significance, is there evidence of a linear relationship between the starting salary upon graduation and program per-year tuition? Determine the hypotheses for the test. H₂ H₂: (Type integers or decimals. Do not round.) Compute the test statistic. The test statistic is ISTAT = (Round to two decimal places needed.) Find the p-value. The p-value is. (Round to three decimal places as needed.) Reach a decision. Hg. There is ✔ evidence to conclude that there is a linear relationship between the starting salary upon graduation and program per-year tuition. b. Construct a 99% confidence interval estimate of the population slope, B.. The confidence interval is≤ ₁, $. (Round to three decimal places as needed.)
Tuition vs. Salary Program Per-Year Mean Starting Salary Tuition ($) Upon Graduation ($) 64,576 153,060 66,839 152,847 67,484 145,078 68,080 146,420 67,385 144,398 66,409 151,576 66,364 146,373 69,872 151,532 63,310 135,921 63,339 147,647 65,272 143,639 II 60,254 147,879 60,928 142,694 56,855 137,717 55,712 121,456 56,486 114,574 55,933 128,707 51,075 132,223 53,197 129,650 50,059 121,399 44,523 112,274 47,645 106,449 50,926 108,274 46,966 108,613 38,712 79,110 X
48,342 47,773 49,756 39,428 33,242 42,661 41,902 48,199 32,926 22,453 41,101 39,789 80,475 99,339 78,620 83,337 71,760 78,050 51,529 64,203 102,587 55,642 77,506 52,654
sufficient, insufficient
A prospective MBA student would like to examine the factors that impact starting salary upon graduation and decides to develop a model that uses program per-year tuition as a predictor of starting salary. Data were collected for 37 full-time MBA programs offered at private universities. The data are stored in the accompanying table. The least-squares regression equation for these data is Y₁ = -14,012.822 +2.428X; and the standard error of the estimate is Syx = 16,131.781. Assume that the straight-line model is appropriate and there are no serious violations the assumptions of the least-squares regression model. Complete parts (a) and (b) below. Click the icon to view the data on program per-year tuition and mean starting salary. a. At the 0.01 level of significance, is there evidence of a linear relationship between the starting salary upon graduation and program per-year tuition? Determine the hypotheses for the test. H₂ H₂: (Type integers or decimals. Do not round.) Compute the test statistic. The test statistic is ISTAT = (Round to two decimal places needed.) Find the p-value. The p-value is. (Round to three decimal places as needed.) Reach a decision. Hg. There is ✔ evidence to conclude that there is a linear relationship between the starting salary upon graduation and program per-year tuition. b. Construct a 99% confidence interval estimate of the population slope, B.. The confidence interval is≤ ₁, $. (Round to three decimal places as needed.)
Tuition vs. Salary Program Per-Year Mean Starting Salary Tuition ($) Upon Graduation ($) 64,576 153,060 66,839 152,847 67,484 145,078 68,080 146,420 67,385 144,398 66,409 151,576 66,364 146,373 69,872 151,532 63,310 135,921 63,339 147,647 65,272 143,639 II 60,254 147,879 60,928 142,694 56,855 137,717 55,712 121,456 56,486 114,574 55,933 128,707 51,075 132,223 53,197 129,650 50,059 121,399 44,523 112,274 47,645 106,449 50,926 108,274 46,966 108,613 38,712 79,110 X
48,342 47,773 49,756 39,428 33,242 42,661 41,902 48,199 32,926 22,453 41,101 39,789 80,475 99,339 78,620 83,337 71,760 78,050 51,529 64,203 102,587 55,642 77,506 52,654