Answer:
0.7125
Step-by-step explanation:
The binomial distribution with parameters n and p is the discrete probability distribution of the number of successes (with probability p) in a sequence of n independent events.
The probability of getting exactly x successes in n independent Bernoulli trials = [tex]n_{C_{x}}(p)^x(1-p)^{n-x}[/tex]
Total number of watches in the shipment = 50
Number of defective watches = 6
Number of selected watches = 10
Let X denotes the number of defective digital watches such that the random variable X follows a binomial distribution with parameters n and p.
So,
Probability of defective watches = [tex]\frac{X}{n}=\frac{6}{50}=0.12[/tex]
Take n = 10 and p = 0.12
Probability that the shipment will be rejected = [tex]P(X\geq 1)=1-P(X=0)[/tex]
[tex]=1-n_{C_{x}}(p)^x(1-p)^{n-x}\\=1-10_{C_{0}}(0.12)^0(1-0.12)^{10-0}[/tex]
Use [tex]n_{C_{x}}=\frac{n!}{x!(n-x)!}[/tex]
So,
Probability that the shipment will be rejected = [tex]=1-\left ( \frac{10!}{0!(10-0)!} \right )(0.88)^{10}[/tex]
[tex]=1-(0.88)^{10}\\=1-0.2785\\=0.7125[/tex]