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.).

College Accounting (Book Only): A Career Approach
13th Edition
ISBN:9781337280570
Author:Scott, Cathy J.
Publisher:Scott, Cathy J.
Chapter11: Work Sheet And Adjusting Entries
Section: Chapter Questions
Problem 8DQ
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It says -2.39 is not correct, what is the correct solution
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
Transcribed Image Text: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.).
Transcribed Image Text: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.).
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