Each sweat shop worker at a computer factory can put together 4.9 computers per hour on average with a standard deviation of 0.8 computers. 47 workers are randomly selected to work the next shift at the factory. Round all answers to 4 decimal places where possible and assume a normal distribution.If one randomly selected worker is observed, find the probability that this worker will put together between 4.7 and 4.8 computers per hour.For the 47 workers, find the probability that their average number of computers put together per hour is between 4.7 and 4.8.Find the probability that a 47 person shift will put together between 220.9 and 225.6 computers per hour.

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Answered: Each sweat shop worker at a computer…

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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Each sweat shop worker at a computer factory can put together 4.9 computers per hour on average with a standard deviation of 0.8 computers. 47 workers are randomly selected to work the next shift at the factory. Round all answers to 4 decimal places where possible and assume a normal distribution.

If one randomly selected worker is observed, find the probability that this worker will put together between 4.7 and 4.8 computers per hour.
For the 47 workers, find the probability that their average number of computers put together per hour is between 4.7 and 4.8.
Find the probability that a 47 person shift will put together between 220.9 and 225.6 computers per hour.

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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