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Q13. Suppose that a certain type of electronic component follows an exponential distribution with a mean life of 500 hours. Let X be the sample average of the life of 25 electronic components. (a) Find the mean and variance of X. (b) Use Chebyshev's inequality to find a lower bound for P(300 < X < 700). (c) Find P(300 < X < 700), by using the central limit theorem and the table of the standard normal cumulative distribution given on the last page.

Q13. Suppose that a certain type of electronic component follows an exponential distribution with a mean life of 500 hours. Let X be the sample average of the life of 25 electronic components. (a) Find the mean and variance of X. (b) Use Chebyshev's inequality to find a lower bound for P(300 < X < 700). (c) Find P(300 < X < 700), by using the central limit theorem and the table of the standard normal cumulative distribution given on the last page.

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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Q13 b and c pls, thank you. 
Mean = 1/500 = 0.002
var(x) = 1/500^2 = 0.000004

Q13. Suppose that a certain type of electronic component follows an exponential distribution with a mean life of 500 hours. Let X be the sample average of the life of 25 electronic components. (a) Find the mean and variance of X. (b) Use Chebyshev's inequality to find a lower bound for P(300 < X < 700). (c) Find P(300 < X < 700), by using the central limit theorem and the table of the standard normal cumulative distribution given on the last page.
Transcribed Image Text:Q13. Suppose that a certain type of electronic component follows an exponential distribution with a mean life of 500 hours. Let X be the sample average of the life of 25 electronic components. (a) Find the mean and variance of X. (b) Use Chebyshev's inequality to find a lower bound for P(300 < X < 700). (c) Find P(300 < X < 700), by using the central limit theorem and the table of the standard normal cumulative distribution given on the last page.
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