A tire company produced a batch of 6 comma 000 tires that includes exactly 220 that are defective. a. If 4 tires are randomly selected for installation on a​ car, what is the probability that they are all​ good? b. If 100 tires are randomly selected for shipment to an​ outlet, what is the probability that they are all​ good? Should this outlet plan to deal with defective tires returned by​ consumers?

Respuesta :

Answer:

a) [tex] P(X=0)[/tex]

Who represent 0 defective and using the probability mass function we got:

[tex] P(X=0) = (4C0) (0.0367)^0 (1-0.0367)^{4-0} = 0.8612[/tex]

b) [tex] P(X=0) = (100C0) (0.0367)^0 (1-0.0367)^{100-0} = 0.02378[/tex]

For this case we can conclude that the outlet plan would deal the defectives returned by consumers

Step-by-step explanation:

Let X the random variable of interest "number of defectives", on this case we now that:  

[tex]X \sim Binom(n, p)[/tex]

the probability of being defective for this case is given by:

[tex] p = \frac{220}{6000}= 0.0367[/tex]  

The probability mass function for the Binomial distribution is given as:  

[tex]P(X)=(nCx)(p)^x (1-p)^{n-x}[/tex]  

Where (nCx) means combinatory and it's given by this formula:  

[tex]nCx=\frac{n!}{(n-x)! x!}[/tex]  

Part a

For this case n = 4 and we want to find this probability:

[tex] P(X=0)[/tex]

Who represent 0 defective and using the probability mass function we got:

[tex] P(X=0) = (4C0) (0.0367)^0 (1-0.0367)^{4-0} = 0.8612[/tex]

Part b

For this case n = 100 and we want to find this probability:

[tex] P(X=0)[/tex]

Who represent 0 defective and using the probability mass function we got:

[tex] P(X=0) = (100C0) (0.0367)^0 (1-0.0367)^{100-0} = 0.02378[/tex]

For this case we can conclude that the outlet plan would deal the defectives returned by consumers