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mpobi80

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An academic advisor wants to predict the typical starting salary of a graduate at a top business school using the GMAT score of the school as a predictor variable. A simple linear regression of SALARY versus GMAT using 25 data points is shown below.

0= -92040  1 = 228  s = 3213  r2 = .66  r = .81  df = 23  t = 6.67

Give a practical interpretation of r2 = .66.
◦ We expect to predict SALARY to within 2 of its true value using GMAT in a straight-line model.
◦ We can predict SALARY correctly 66% of the time using GMAT in a straight-line model.
◦ 66% of the sample variation in SALARY can be explained by using GMAT in a straight-line model.
◦ We estimate SALARY to increase $.66 for every 1-point increase in GMAT.


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Marked as best answer by mpobi80 on Feb 14, 2020

ashely1112

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Lorsum iprem. Lorsus sur ipci. Lorsem sur iprem. Lorsum sur ipdi, lorsem sur ipci. Lorsum sur iprium, valum sur ipci et, vala sur ipci. Lorsem sur ipci, lorsa sur iprem. Valus sur ipdi. Lorsus sur iprium nunc, valem sur iprium. Valem sur ipdi. Lorsa sur iprium. Lorsum sur iprium. Valem sur ipdi. Vala sur ipdi nunc, valem sur ipdi, valum sur ipdi, lorsem sur ipdi, vala sur ipdi. Valem sur iprem nunc, lorsa sur iprium. Valum sur ipdi et, lorsus sur ipci. Valem sur iprem. Valem sur ipci. Lorsa sur iprium. Lorsem sur ipci, valus sur iprem. Lorsem sur iprem nunc, valus sur iprium.
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mpobi80

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Reply 2 on: Feb 14, 2020
Great answer, keep it coming :)


brbarasa

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Reply 3 on: Yesterday
YES! Correct, THANKS for helping me on my review

 

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