Answer Happy

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 results are displayed in the accompanying table, and the regression equation and other values are provided. Use this information to complete parts (a) through (c) below. ₁-10,117.5+2.3633X, n ΣΥ=4,223,698, Σγ = 520,314,669,642, Σ ΧΥ = 234,271,473,095 i=1 Click the icon to view the data table. a. Determine the coefficient of determination, 2, and interpret its meaning. =(Round to four decimal places as needed.) What is the meaning of the coefficient of determination? A. It measures the variability in the actual starting salary from the predicted per-year tuition. B. It measures the variability in the actual per-year tuition from the predicted number of starting salary.
OC. It is the proportion of the variation in per-year tuition that is explained by the variability in starting salary. OD. It is the proportion of the variation in starting salary that is explained by the variability in per-year tuition. b. Determine the standard error of the estimate. Syx = (Round to two decimal places as needed.) c. How useful do you think this regression model is for predicting starting salary? Since the value of r² is the regression model is for predicting starting salary.
MBA Data Program Per-Year Tuition ($) 62,315 67,707 66,890 67,543 66,591 67,506 67,465 69,825 63,381 62,521 67,518 61,367 62,130 56,321 54,416 56,503 56,436 52,028 53,435 49,602 45,968 46,424 51,072 47,312 37,682 10 125 Mean Starting Salary Upon Graduation ($) 155,395 152,869 147,317 144,489 144,523 156,343 149,433 149,723 133,493 145,155 143,845 146,674 139,955 40,935 122,291 113,750 125,426 130,699 130,985 124,771 112,593 109,150 110,281 105,877 77,907 90 210
37,682 49,135 45,627 51,415 37,578 33,526 41,989 40,446 48,041 33,025 23,129 42,973 38,745 77,907 80,349 104,477 75,081 87,351 74,899 77,563 52,902 67,316 101,928 58,707 77,823 51,423