Answer:
a) 0.164 = 16.4% probability that a disk has exactly one missing pulse
b) 0.017 = 1.7% probability that a disk has at least two missing pulses
c) 0.671 = 67.1% probability that neither contains a missing pulse
Step-by-step explanation:
To solve this question, we need to understand the Poisson distribution and the binomial distribution(for item c).
Poisson distribution:
In a Poisson distribution, the probability that X represents the number of successes of a random variable is given by the following formula:
![P(X = x) = \frac{e^{-\mu}*\mu^{x}}{(x)!} ](https://tex.z-dn.net/?f=P%28X%20%3D%20x%29%20%3D%20%5Cfrac%7Be%5E%7B-%5Cmu%7D%2A%5Cmu%5E%7Bx%7D%7D%7B%28x%29%21%7D%0A)
In which
x is the number of sucesses
is the Euler number
is the mean in the given interval.
Binomial distribution:
The binomial probability is the probability of exactly x successes on n repeated trials, and X can only have two outcomes.
In which
is the number of different combinations of x objects from a set of n elements, given by the following formula.
And p is the probability of X happening.
Poisson mean:
![\mu = 0.2](https://tex.z-dn.net/?f=%5Cmu%20%3D%200.2)
a. What is the probability that a disk has exactly one missing pulse?
One disk, so Poisson.
This is P(X = 1).
![P(X = 1) = \frac{e^{-0.2}*0.2^{1}}{(1)!} = 0.164 ](https://tex.z-dn.net/?f=P%28X%20%3D%201%29%20%3D%20%5Cfrac%7Be%5E%7B-0.2%7D%2A0.2%5E%7B1%7D%7D%7B%281%29%21%7D%20%3D%200.164%0A)
0.164 = 16.4% probability that a disk has exactly one missing pulse
b. What is the probability that a disk has at least two missing pulses?
![P(X \geq 2) = 1 - P(X < 2)](https://tex.z-dn.net/?f=P%28X%20%5Cgeq%202%29%20%3D%201%20-%20P%28X%20%3C%202%29)
In which
![P(X < 2) = P(X = 0) + P(X = 1)](https://tex.z-dn.net/?f=P%28X%20%3C%202%29%20%3D%20P%28X%20%3D%200%29%20%2B%20P%28X%20%3D%201%29)
In which
![P(X = x) = \frac{e^{-\mu}*\mu^{x}}{(x)!} ](https://tex.z-dn.net/?f=P%28X%20%3D%20x%29%20%3D%20%5Cfrac%7Be%5E%7B-%5Cmu%7D%2A%5Cmu%5E%7Bx%7D%7D%7B%28x%29%21%7D%0A)
![P(X = 0) = \frac{e^{-0.2}*0.2^{0}}{(0)!} = 0.819](https://tex.z-dn.net/?f=P%28X%20%3D%200%29%20%3D%20%5Cfrac%7Be%5E%7B-0.2%7D%2A0.2%5E%7B0%7D%7D%7B%280%29%21%7D%20%3D%200.819)
![P(X = 1) = \frac{e^{-0.2}*0.2^{1}}{(1)!} = 0.164 ](https://tex.z-dn.net/?f=P%28X%20%3D%201%29%20%3D%20%5Cfrac%7Be%5E%7B-0.2%7D%2A0.2%5E%7B1%7D%7D%7B%281%29%21%7D%20%3D%200.164%0A)
![P(X < 2) = P(X = 0) + P(X = 1) = 0.819 + 0.164 = 0.983](https://tex.z-dn.net/?f=P%28X%20%3C%202%29%20%3D%20P%28X%20%3D%200%29%20%2B%20P%28X%20%3D%201%29%20%3D%200.819%20%2B%200.164%20%3D%200.983)
![P(X \geq 2) = 1 - P(X < 2) = 1 - 0.983 = 0.017](https://tex.z-dn.net/?f=P%28X%20%5Cgeq%202%29%20%3D%201%20-%20P%28X%20%3C%202%29%20%3D%201%20-%200.983%20%3D%200.017)
0.017 = 1.7% probability that a disk has at least two missing pulses
c. If two disks are independently selected, what is the probability that neither contains a missing pulse?
Two disks, so binomial with n = 2.
A disk has a 0.819 probability of containing no missing pulse, and a 1 - 0.819 = 0.181 probability of containing a missing pulse, so ![p = 0.181](https://tex.z-dn.net/?f=p%20%3D%200.181)
We want to find P(X = 0).
0.671 = 67.1% probability that neither contains a missing pulse