Respuesta :
Answer:
a) 0.7403
b)0.0498
c)0.2240
Step-by-step explanation:
Given: The number of surface flaws in plastic panels used in the interior of automobiles has a Poisson distribution
We know that to calculate expected number of flaws use
expected number of flaws =10×0.03 =0.3
a) probability that there are no surface flaws in an auto's interior =P(X=0)=
e^-0.3 =0.7408
b) probability that none of the 10 cars has any surface flaws =(e^-0.3)^10 =0.0498
c) probability that at most one car has any surface flaws =P(X<=1)=P(X=0)+P(X=1)
this means
=10C_0(1-0.7408)^0(0.7408)^10+10C_1(1-0.7408)^1(0.7408)^9=0.2240
Answer:
a) 0.4065
b) 0.000126
c) 0.001921
Step-by-step explanation:
Given data:
Poisson distribution mean = 0.06
Amount of plastic panel = 10 square panel
Probability mass function given by Poisson distribution is
[tex]P(X =x) = \frac{e^{-\lambda} \lambda^x}{x!}[/tex] x: 0,1,2,......
where [tex]\lambda[/tex] is parameter
here lambda is 0.06 per square ft
[tex]\lambda = 0.09\times 10 = 0.9 pe\ 10\ square\ foot[/tex]
a) from Poisson distribution
[tex]P(X =x) = \frac{e^{-\lambda} \lambda^x}{x!}[/tex]
[tex]= \frac{e^{-0.9} \lambda^0}{0!}[/tex]
[tex]= e^{-0.9} = 0.4065[/tex]
B) PROBABILITY OF NO SURFACE FLAWS IN CAR
N = 10
p = 1 - 0.406 = 0.5934
q = 0.4065
[tex]P(X =x) =\binom{n}{x} p^x q^{n-x}[/tex]
[tex]=\binom{10}{0} 0.59^0 0.4065^{10-0}[/tex]
= 0.000126
c) probability of 1 car flaw
[tex]P(X \leq 1) = P(X = 0) + P(X = 1)[/tex]
[tex]= ^{10}C_0 (1 - 4065)^0 (0.4065)^{10} + ^{10}C_1 (1 - 4065)^1 (0.4065)^{9}[/tex]
[tex]= 1 \times 1.231\times 10^{-4} + 10\times 0.5935\times 3.030\times 10^{-4}[/tex]
= 0.001921