This scenario can be described by a binomial distribution because the experiment results in an outcome that can be classified as either a success or failure. For this case, the test results in either a student being Covid-19 positive(success) or Covid-19 negative(failure).
Let "X" be a random variable representing the number of Covid-19 patients, "n" be the number of trials, "x" be the number of successes out of "n" trials and "p" be the probability of success.
Therefore, out of "n=8" students, the number of successes are "x=3" and the probability of success "p=(x\/n)=3\/8". The probability of failure is given as "q=1-p=1-3\/8=5\/8" .
The probability distribution of the random variable "X" is given by the formula,
"p(X=x)=\\binom{8}{x}p^x(1-p)^{n-x},\\space x=0,1,2,3,4,5,6,7,8"
"0,\\space elsewhere"
If a random test was done on 2 students then, probability that they were both Covid-19 positive is given as,
"p(X=2)=\\binom{8}{2}(3\/8)^{2}*(5\/8)^6=0.2346933"
The probability that both are Covid-19 negative is "1-0.2346933=0.7653067".
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