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Most graduate schools of business require applicants for admission to take the Graduate Management Admission Council's GMAT examination. Scores on the GMAT are roughly normally distributed with a mean of 527 and a standard deviation of 112. 1. What is the probability of an individual scoring above 500 on the GMAT? 2. How high must an individual score on the GMAT in order to score in the highogt 50%?

Most graduate schools of business require applicants for admission to take the Graduate Management Admission Council's GMAT examination. Scores on the GMAT are roughly normally distributed with a mean of 527 and a standard deviation of 112. 1. What is the probability of an individual scoring above 500 on the GMAT? 2. How high must an individual score on the GMAT in order to score in the highogt 50%?

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Most graduate schools of business require applicants for admission to take the Graduate Management Admission Council's GMAT examination. Scores on the GMAT are roughly normally distributed with a mean of 527 and a standard deviation of 112. 1. What is the probability of an individual scoring above 500 on the GMAT? 2. How high must an individual score on the GMAT in order to score in the highest 5%? Do all calculations in terms of the standard normal distribution using location-scale proper- ties. You can compute the final number in R using pnorm and qnorm.
Transcribed Image Text:Most graduate schools of business require applicants for admission to take the Graduate Management Admission Council's GMAT examination. Scores on the GMAT are roughly normally distributed with a mean of 527 and a standard deviation of 112. 1. What is the probability of an individual scoring above 500 on the GMAT? 2. How high must an individual score on the GMAT in order to score in the highest 5%? Do all calculations in terms of the standard normal distribution using location-scale proper- ties. You can compute the final number in R using pnorm and qnorm.
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