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an experiment whose outcome is random and can be either of two possible outcomes, "success" or "failure"
At ABC College, the withdrawal rate from an elementary physics course is 30% for any given term.
This implies that, for any given term, 70% of the students stay in the class for the entire term.
A "success" could be defined as an individual who withdrew.
The random variable is X = the number of students who withdraw from the randomly selected elementary physics class.
Many random experiments include counting the number of successes in a series of a fixed number of independently repeated trials, which may result in either success or failure.
The distribution of the number of successes is a binomial distribution.
It is a discrete probability distribution with two parameters, traditionally indicated by n, the number of trials, and p, the probability of success.
Such a success/failure experiment is also called a Bernoulli experiment, or Bernoulli trial; when n = 1, the Bernoulli distribution is a binomial distribution.
Named after Jacob Bernoulli, who studied them extensively in the 1600s, a well known example of such an experiment is the repeated tossing of a coin and counting the number of times "heads" comes up.
In a sequence of Bernoulli trials, we are often interested in the total number of successes and not in the order of their occurrence.
If we let the random variableX equal the number of observed successes in n Bernoulli trials, the possible values of X are 0,1,2,…,n.
If x success occur, where x=0,1,2,...,n , then n-x failures occur.
The number of ways of selecting x positions for the x successes in the x trials is:
Since the trials are independent and since the probabilities of success and failure on each trial are, respectively, p and q=1−p, the probability of each of these ways is px(1−p)n−x.
Thus, the p.d.f. of X, say f(x) , is the sum of the probabilities of these (nx)mutually exclusive events--that is,
These probabilities are called binomial probabilities, and the random variableX is said to have a binomial distribution .
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