in a binomial probability experiment with probability of success

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(..

A random experiment which has only two outcomes (success or failure) Let n independent bernoulli trials be performed and X denote the number of successes in n trials then X follows a binomial distribution. The probability of success b..

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 ..

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: 1. Number of trials n tend..

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..

We have P(X = x + 1) = n C x + 1 p x + 1 q n - x - 1 ..

Random Experiment and Sample Space - An experiment repeated under essentially homogeneous and similar conditions results in an outcome, which is unique or not unique but may be one of the several possible outcomes. When the result is unique then the experiment is calle..

>There are many daily life situations where n is very large and p is very small. In such situations, the Poisson distribution can be more conveniently used as an approximation to binomial distriburtion which may prove cumbersome for large values of n. This is called Poisson approximation ..

Conclusion - 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 Poisso..

Let A and B be any two events associated with a random experiment. The probability of occurrence of event A when the event B has already occurred is called the conditional probability of A when B is given and is denoted as P(A/B..