Program Per-Year Tuition ($) Mean Starting Salary Upon Graduation ($) 64089 154659 66648 153322 65918 146231 67691 143072 65258 139285 67795 156063 66305 148827 67646 147938 62858 133303 64167 146732 65969 144175 60577 144238 61434 140276 55740 136345 56190 126696 55702 116433 56184 128352 51092 127971 51876 129581 51611 125360 46116 113747 48220 111027 48721 109007 45610 107616 36891 78039 46472 77593 47927 103934 48853 74243 38875 87372 34156 75301 43287 75873 42784 54149 48738 63567 34783 103729 21954 53787 42129 81279 40028 55704 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 = 13,863.426 +2.437X, and the standard error of the estimate is Syx 15,910.578. 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. Ho P₁ H₁ B₁ # 0 (Type integers or decimals. Do not round.) Compute the test statistic. The test statistic is ISTAT --2.39 (Round to two decimal places as needed.).