Question 4 [16 Marks]
Research has shown that about 2% of all products produced by BVH Company are defective. A quality
inspector has just sampled 300 products from this company. Using the Poisson distribution, what is the
probability that:
(a) exactly 12 of them are defective? [4]
(b) at least 8 of them are defective?
We need to establish the relationship between binomial distribution and Poisson distribution because finding probabilities for number of defectives requires the use of binomial distribution.
Here,
"n=300"
"p=2\\%=2\/100=0.02"
Relationship between these two distributions is that parameter "\\lambda" for a Poisson distribution is the mean of Binomial distribution. This relationship can be written as,
"\\lambda=np" where "np" id the mean of a Binomial random varible.
Express by "X" the number of defectives produced by BVH company then, "X\\sim Poisson(\\lambda)" and its probability mass function is given as,
"p(X=x)=e^{(-\\lambda)}(\\lambda)^x\/{x}!"
The value of "\\lambda" is given as,
"\\lambda=n*p=0.02*300=6"
a.
Probability of exactly 12 defectives is written as,
"p(X=12)=e^{-6}(6)^{12}\/12!"
By running this command in "R",
"dpois(12,6)= 0.01126448"
Therefore, the probability that there are exactly 12 defectives is 0.01126448
b.
The probability that there are at least 8 defectives is given as,
"p(X\\geqslant8)=1-p(X\\lt8)=1-\\displaystyle\\sum^7_{x=0}(e^{-6}6^x)\/x!"
Again, we use run the following commands in "R"
"p(X\\geqslant8)=1-ppois(7,6)=1-0.7439798= 0.2560202"
Therefore, the probability that there are at least 8 defectives is 0.2560202
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