Question 21: a requirement for business graduate school is the GMAT. The GMAT is normally distributed with a mean of 527 and a standard deviation of 112. The max score on the GMAT score is 800. Calculate the probability a test taker scores higher that a 527 on the exam. (Hint: Watch the max score. Round to the hundredths.) A requirement for business graduate school is the GMAT. TheGMAT is normally distributed with a mean of 527 and astandard deviation of 112. The max score on the GMAT is 800.Calculate the probability a test taker scores higher that a 527on the exam. (Hint: Watch the max score. Round to thehundredths).0.500.910.87O 0.49

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Answered: A requirement for business graduate…

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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Question 21: a requirement for business graduate school is the GMAT. The GMAT is normally distributed with a mean of 527 and a standard deviation of 112. The max score on the GMAT score is 800. Calculate the probability a test taker scores higher that a 527 on the exam. (Hint: Watch the max score. Round to the hundredths.)

A requirement for business graduate school is the GMAT. The
GMAT is normally distributed with a mean of 527 and a
standard deviation of 112. The max score on the GMAT is 800.
Calculate the probability a test taker scores higher that a 527
on the exam. (Hint: Watch the max score. Round to the
hundredths).
0.50
0.91
0.87
O 0.49

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

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