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An MBA Admissions Officer Wishes to Predict an MBA Applicant's

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An MBA admissions officer wishes to predict an MBA applicant's grade point average (GPA) for the MBA program on the basis of the applicant's score on the Graduate Management Admission Test (GMAT) and their undergraduate GPA (UGPA) . The admissions officer used a random sample of previously admitted applicants to build a regression tree that can be used to predict the MBA GPAs of future MBA students. Below is the final regression tree. An MBA admissions officer wishes to predict an MBA applicant's grade point average (GPA)  for the MBA program on the basis of the applicant's score on the Graduate Management Admission Test (GMAT)  and their undergraduate GPA (UGPA) . The admissions officer used a random sample of previously admitted applicants to build a regression tree that can be used to predict the MBA GPAs of future MBA students. Below is the final regression tree.   Based on this regression tree, how many of the admitted applicants in the sample had a GMAT score of less than 650? A)  96 B)  453 C)  507 D)  549 E)  There is insufficient information to determine the answer. Based on this regression tree, how many of the admitted applicants in the sample had a GMAT score of less than 650?


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Perfect Information

A condition in decision theory and economics where all participants have full and identical knowledge about the actions others can take.

Power Company

A corporation that generates, transmits, and distributes electricity to consumers and businesses.

Expected Payoff

In decision theory and economics, the weighted average of all possible outcomes of a decision, where each outcome is weighted by its respective probability of occurrence.

Perfect Information

A situation where all participants have full and equal knowledge about the game structure, strategies, and outcomes in decision-making scenarios.

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