Random Variable and Probability Distribution
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 variables are 1. Co..
Discrete probability distribution
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 X : x 1 x 2 x 3 x n P(X) : p 1 p 2 ..
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 X : x 1 x 2 x 3 x n P(X) : p 1 p 2 ..Probability (continued) Conclusion
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 ..
Probability - I Summary
>If A, B and C are mutually exclusive then Total Probability: P(A) = P(E 1 ) P(A|E 1 ) + P(E 2 ) P(A|E 2 )+ +P(E n ) P(A|E n ) Random variable: A real valued function 'X' defined on the sample space is called a random variable. Discrete ra..
>If A, B and C are mutually exclusive then Total Probability: P(A) = P(E 1 ) P(A|E 1 ) + P(E 2 ) P(A|E 2 )+ +P(E n ) P(A|E n ) Random variable: A real valued function 'X' defined on the sample space is called a random variable. Discrete ra..Summary
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 probability distribution of X. 2. ..
Mean and Variance of a Discrete Random Variable
Let X be a discrete random variable which can assume values x 1 , x 2 , x 3 ,x n with probabilities p 1 , p 2 , p 3 .. p n respectively then (a) Mean of X or expectation of X denoted by E(X) or m is given by (b) Variance of X denoted by s 2 is given ..
Let X be a discrete random variable which can assume values x 1 , x 2 , x 3 ,x n with probabilities p 1 , p 2 , p 3 .. p n respectively then (a) Mean of X or expectation of X denoted by E(X) or m is given by (b) Variance of X denoted by s 2 is given ..Random Variables and Probability Distributions
Random Variables and Probability Distributions - It 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. Ou..
Random Variables and Probability Distributions
It 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 random variable..
Probability distribution of a continuous random variable
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 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 ..Note:
There can be several r.v's associated with an experiment. A random variable which can assume only a finite number of values or countably infinite values is called a discrete random variable. e.g., Consider a random experiment of tossing t..
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