in a binomial distribution the random variable x is continuous

Let X be continuous random variable which can assume values in the interval [a,b]. A function f(x) on [a,b] is called the probability density function if ..

Let S be a sample space associated with a given random experiment. A real valued function X which assigns to each w i S, a unique real number, X( w i ) = x i is called a random variable . Two types of random..

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 ..

Random Variable and Probability Distribution - If is often very important to allocate a numerical value to an outcome of a random experiment. For example consider an experiment of tossing a coin twice and note the number of heads (x) obtained. Outco..

If is often very important to allocate a numerical value to an outcome of a random experiment. For example consider an experiment of tossing a coin twice and note the number of heads (x) obtained. Outcome : HH HT TH TT No. of heads (x) : 2 1 1 0 x is called a..

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 distribu..

If we consider the body with continuous distribution of matter, the summation in the formula of centre of mass should be replaced by integration. Therefore, we do not talk of the i t h particle, rather, we talk of a small element of the body having a mass dm. If x, ..

A discrete random variable assumes each of its values with a certain probability. Let X be a discrete random variable which takes values x 1 , x 2 , x 3 ,x n where p i = P{X = x i } Then..

Although the probability distribution of a continuous random variable cannot be presented in tabular form, it can have a formula in the form of a function represented by f(x) usually called the probability density functio..

1. If x is a discrete random variable assuming the values x 1 , x 2 , x 3 ,.,x n with probabilities p 1 , p 2 , p 3 ,., p n respectively then (x 1 ,p 1 ), (x 2 , p 2 ),(x n , p n ) defines a ..