Respuesta :
The probability that the sample proportion of airborne viruses in differ from the population proportion by greater than 3% is 0.006.
According to the Central limit theorem, if from an unknown population large samples of sizes n > 30, are selected and the sample proportion for each sample is computed then the sampling distribution of sample proportion follows a Normal distribution.
The mean of this sampling distribution of sample proportion is:
μρ=ρ
The standard deviation of this sampling distribution of sample proportion is:
σρ=[tex]\sqrt \frac{p(1-p)}{n}[/tex]
The information provided is:
n = 533
p = 0.09
As the sample size is quite large, i.e. n = 533 > 30, the central limit theorem can be used to approximate the sampling distribution of sample proportion by a Normal distribution.
The mean and standard deviation are:
μρ=ρ=0.09
σρ=[tex]\sqrt \frac{p(1-p)}{n}[/tex]=[tex]\sqrt\frac{0.09(1-0.09)}{533}=0.01239[/tex]
Compute the probability that the sample proportion of airborne viruses in differ from the population proportion by greater than 3% as follows:
[tex]p(p^-p > 0.03)=P(p^ > 0.12) \\=P(z > \frac{0.12-0.9}{0.012}) \\= P(Z > 2.5) \\= 1-P(Z > 2.5) \\ = 1- 0.993 \\ = 0.00621[/tex]
Thus, the probability that the sample proportion of airborne viruses in differ from the population proportion by greater than 3% is 0.006.
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