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olchik [2.2K]
3 years ago
5

In a certain​ four-engine vintage​ aircraft, now quite​ unreliable, each engine has a 15​% chance of failure on any​ flight, as

long as it is carrying its​ one-fourth share of the load. But if one engine​ fails, then the chance of failure increases to 35​% for each of the other three engines. And if a second engine​ fails, each of the remaining two has a 45​% chance of failure. Assuming that no two engines ever fail​ simultaneously, and that the aircraft can continue flying with as few as two operating​ engines, find the probability of exactly one engine failure.
Mathematics
1 answer:
Romashka [77]3 years ago
8 0

Answer:

0.0975 or 9.75%

Step-by-step explanation:

Assuming that no engines fail simultaneously, the probability that exactly one engine fails is the probability that the first engine fails (15%) multiplied by the probability that the second engine does not fail (100% - 35%):

P = 0.15*(1-0.35)\\P=0.0975

The probability of exactly one engine failure is 0.0975 or 9.75%

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murzikaleks [220]

Answer:

The calculated value of z = - 0.197  falls in the critical region therefore we reject the null hypothesis and conclude that  at  the 5% significance level there is significant difference in population proportions of households that decorate their houses with lights for the holidays

Step-by-step explanation:

We formulate the null and alternative hypotheses as

H0: p1= p2 there is no difference in population proportions of households that decorate their houses with lights for the holidays

against Ha : p1≠ p2  (claim)  ( two sided)

The significance level is set at ∝= 0.05

The critical value for two tailed test at alpha=0.05 is ± 1.96

or Z∝= 0.05/2= ± 1.96

The test statistic is

Z = p1-p2/√pq(1/n1 +1/n2)

p1= proportions of households  decorating in city 1  = 45/60=0.75

p2= proportions of households  decorating in city 2 = 40/50= 0.8

p = the common proportion on the assumption that the two proportion are same.

p =   \frac{n_1p_1 +n_2p_2}{n_1+n_2}

Calculating

p =60 (0.75) + 50 (0.8) / 110

p=  45+ 40/110= 85/110 = 0.772

so  q = 1-p= 1- 0.772= 0.227

Putting the values in the test statistic and calculating

z= 0.75- 0.8/ √0.772*0.227( 1/60 + 1/50)

z= -0.05/√ 0.175244 ( 110/300)

z= -0.05/0.25348

z= -0.197

The calculated value of z = - 0.197  falls in the critical region therefore we reject the null hypothesis and conclude that  at  the 5% significance level there is significant difference in population proportions of households that decorate their houses with lights for the holidays

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