A) You need to use the binomial distribution, for which the probability of an event X is given by:
[tex]P(X) = \frac{n!}{k!(n-k)!} p^{k} (1-p)^{n-k} [/tex]
where:
n = total number of events
k = number of success we want
p = probability of success
Therefore, since the problem tells you that X is the number of subjects who test positive for the disease, you will have:
[tex]P(X) = \frac{30!}{0!(30-0)!} 0.02^{0} (1-0.02)^{30-0} [/tex]
= 1 · 1 · 0.98³⁰
= 0.5455
Hence, the probability of none of the 30 subjects testing positive to the desease is 54.55%
B) In a binomial distribution, the mean is given by the formula:
μ = n · p
= 30 · 0.02
= 0.6
And the standard deviation is given by the formula:
σ = √[n·p·(1-p)]
= √[30·0.02·0.98]
= √0.588
= 0.77
Hence, the mean is 0.6 and the standard deviation is 0.77
C) This test is not very viable: 30 subjects are a sample too small compared to the population (millions of people who need to be tested), the probability of finding that all the 30 subjects are healty is only a little bit over 50%, the standard deviation is too high compared to the mean, and 2% of false positive is a percentage too high to consider the test viable.
