formula for binomial probability

A trial, which has only two outcomes i.e., "a success" or "a failure", is called a Bernoulli trial . The probability distribution of the number of successes, so obtained is called the binomial distribution..

A trial, which has only two outcomes i.e., "a success" or "a failure", is called a Bernoulli trial. Let X be the number of successes in a Bernoulli trial, then X can take 0 or 1 and P(X =1) = p = "probability of a success" P(X = 0) = 1 - p = q = "probability of failure". Conside..

Introduction - Suppose the two events are not independent, that is the occurrence of one depends on the occurrence of other, then how do we compute This can be explained by conditional probability. Baye's theorem is named after the British mathematician Thomas Bayes who published it in a ..

n and p are called the parameters of the binomial distributio..

If the mean and variance of a binomial distribution are respectively 9 and 6, find the distributio..

In this chapter we have studied the method of evaluating probabilities of events relating to independent events and conditional events. We have also studied about random variables and their probability distributions, namely binomial distribution and Poisson distributio..

In this chapter we have studied the method of evaluating probabilities of events relating to independent events and conditional events. We have also studied about random variables and their probability distributions, namely binomial distribution and Poisson..

Mean of a binomial distribution = np = 9 Variance of a binomial distribution = npq = 6 Binomial distribution is given by..

Poisson distribution is a limiting process of binomial distribution. Poisson distribution occurs when there are events which do not occur as outcomes of a definite number of outcomes. Poisson distribution is used under the following conditions: Number of trials n tends to infinity Pr..

Let X be the random variable which represents number of defective items selected which has a binomial distribution with n = 10, p = 0.1, q = 0.9 Probability that the guarantee is satisfied = ..