Lets denote p = percentage of faulty items produced and n = 200.
Because of the manufacturer claim:
"H_0:p= 0.01"
"H_1:p\\neq0.01"
Significance level "\\alpha=0.01"
A Poisson distribution with "\\lambda=np" provides an approximation to a binomial distribution when "n\\ge 50" and "p\\le0.1"
Thus X denotes the number of faulted items in the sample, then
"X\\sim Po(\\lambda=200\\cdot0.01=2)"
Using tables of the Cumulative Poisson Distribution Functions
"P(X\\ge 8)=1-P(X\\le7)=1-0.9989=0.0011"
Since the test is two-tailed this probability is compared with "\\frac{\\alpha}{2}=0.005" because a small number of faulted items could also lead to the rejection of the null hypothesis.
Here, "0.0011<0.005" so "H_0" is rejected.
There is evidence with a 1% level of significance, that the manufacturer's claim is not valid.
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