The probability that the transistor will last between 12 and 24 weeks is 0.424
X= lifetime of the transistor in weeks E(X)= 24 weeks
O,= 12 weeks
The anticipated value, variance, and distribution of the random variable X were all provided to us. Finding the parameters alpha and beta is necessary before we can discover the solutions to the difficulties.
X~gamma(
)
E(X)= 
= 
=6 weeks
V(x)= 
=24/6= 4
Now we can find the solutions:
The excel formula used to create Figure one is as follows:
=gammadist(X, , , False)
P(
)
P(
)
P(
)
P= 0.424
Therefore, probability that the transistor will last between 12 and 24 weeks is 0.424
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The statement is True, Monte Carlo simulation generate many outcomes that are organized into a frequency distribution.
Monte Carlo simulation
- When the possibility of random variables is available, a Monte Carlo simulation is a model that is used to forecast the likelihood of a variety of events. Monte Carlo simulations assist in illuminating how risk and uncertainty affect forecasting and prediction models
- The potential accuracy of a Monte Carlo simulation is roughly 4%, which is still higher than the 1% accuracy stated by SAMPLE, even for a random function with a 3 error factor.
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First, you have to change 7 1/3 to an improper fraction which is 22/3.
Then you have to flip the fraction upside down to get the reciprocal.
So the answer is 3/22
