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Complete Question
The Brown's Ferry incident of 1975 focused national attention on the ever-present danger of fires breaking out in nuclear power plants. The Nuclear Regulatory Commission has estimated that with present technology there will be on average, one fire for every 10 years for a reactor. Suppose that a certain state has two reactors on line in 2020 and they behave independently of one another. Assuming the incident of fires for individual reactors can be described by a Poisson distribution, what is the probability that by 2030 at least two fires will have occurred at these reactors?
Answer:
The value is 
Step-by-step explanation:
From the question we are told that
The rate at which fire breaks out every 10 years is
Generally the probability distribution function for Poisson distribution is mathematically represented as

Here x represent the number of state which is 2 i.e 
Generally the probability that by 2030 at least two fires will have occurred at these reactors is mathematically represented as

=> ![P(x_1 + x_2 \ge 2 ) = 1 - [P(x_1 + x_2 = 0 ) + P( x_1 + x_2 = 1 )]](https://tex.z-dn.net/?f=P%28x_1%20%2B%20x_2%20%5Cge%202%20%29%20%3D%20%201%20-%20%5BP%28x_1%20%2B%20x_2%20%3D%200%20%29%20%2B%20P%28%20x_1%20%2B%20x_2%20%3D%201%20%29%5D)
=> ![P(x_1 + x_2 \ge 2 ) = 1 - [ P(x_1 = 0 , x_2 = 0 ) + P( x_1 = 0 , x_2 = 1 ) + P(x_1 , x_2 = 0)]](https://tex.z-dn.net/?f=P%28x_1%20%2B%20x_2%20%5Cge%202%20%29%20%3D%20%201%20-%20%5B%20P%28x_1%20%20%3D%200%20%2C%20%20x_2%20%3D%200%20%29%20%2B%20P%28%20x_1%20%3D%200%20%2C%20x_2%20%3D%201%20%29%20%2B%20P%28x_1%20%2C%20x_2%20%3D%200%29%5D)
=> 
=> ![P(x_1 + x_2 \ge 2 ) = 1 - \{ [ \frac{1^0}{ 0! } * e^{-1}] * [[ \frac{1^0}{ 0! } * e^{-1}]] )+ ( [ \frac{1^1}{1! } * e^{-1}] * [[ \frac{1^1}{ 1! } * e^{-1}]] ) + ( [ \frac{1^1}{ 1! } * e^{-1}] * [[ \frac{1^0}{ 0! } * e^{-1}]]) \}](https://tex.z-dn.net/?f=P%28x_1%20%2B%20x_2%20%5Cge%202%20%29%20%3D%20%201%20-%20%5C%7B%20%5B%20%5Cfrac%7B1%5E0%7D%7B%200%21%20%7D%20%2A%20e%5E%7B-1%7D%5D%20%2A%20%5B%5B%20%5Cfrac%7B1%5E0%7D%7B%200%21%20%7D%20%2A%20e%5E%7B-1%7D%5D%5D%20%29%2B%20%28%20%5B%20%5Cfrac%7B1%5E1%7D%7B1%21%20%7D%20%2A%20e%5E%7B-1%7D%5D%20%2A%20%5B%5B%20%5Cfrac%7B1%5E1%7D%7B%201%21%20%7D%20%2A%20e%5E%7B-1%7D%5D%5D%20%29%20%2B%20%28%20%5B%20%5Cfrac%7B1%5E1%7D%7B%201%21%20%7D%20%2A%20e%5E%7B-1%7D%5D%20%2A%20%5B%5B%20%5Cfrac%7B1%5E0%7D%7B%200%21%20%7D%20%2A%20e%5E%7B-1%7D%5D%5D%29%20%5C%7D)
=> ![P(x_1 + x_2 \ge 2 )= 1- [[0.3678 * 0.3679] + [0.3678 * 0.3679] + [0.3678 * 0.3679] ]](https://tex.z-dn.net/?f=P%28x_1%20%2B%20x_2%20%5Cge%202%20%29%3D%201-%20%5B%5B0.3678%20%20%2A%200.3679%5D%20%2B%20%5B0.3678%20%20%2A%200.3679%5D%20%2B%20%5B0.3678%20%20%2A%200.3679%5D%20%20%5D)

Answer:
area = 102 ft²
Step-by-step explanation:
(8x6) + (9x6) = 48 + 54 = 102 ft²
Answer:
a) 95% confidence interval estimate of the true weight is (3.026, 3.274)
b) 99% confidence interval estimate of the true weight is (2.944, 3.356)
Step-by-step explanation:
Confidence Interval can be calculated using M±ME where
- M is the mean of five successive weightings (3.150)
- ME is the margin of error from the mean
And margin of error (ME) can be calculated using the formula
ME=
where
- t is the corresponding statistic in the given confidence level and degrees of freedom(t-score)
- s is the standard deviation of the random error (0.1)
Using the numbers 95% confidence interval estimate of the true weight is:
3.150±
≈3.150±0.124
And 99% confidence interval estimate of the true weight is:
3.150±
≈3.150±0.206