probability


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Multiplication Rule of Probability
Events are said to be independent if the occurrence of one event does not affect the occurrence of others. If A and B are two independent events, then This is known as Multiplication Rule of Probability . The converse is also true, that is if two events A and B asso..
Probability (continued) Introduction
Introduction - From our earlier chapter we know that, in statistical experiments, if the events A and B are independent, then But 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..
Random Variable and Probability Distribution
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. Outcome : HH HT TH TT No. of heads (x) : 2 1 ..
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 p 3 . . . . . p n is called the probabilityh..
Random Variables and Probability Distributions
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. Continuous random variable, 2. discrete random varia..
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, which can assume the valu..
Theorem: (Law of Total Probability)
If B 1 , B 2 , B 3 , .., B n are mutually exclusive and exhaustive events of the sample space S, then for any event A of ..
Probability (continued) Summary
Summary - P {Occurrence of A given that B has occurred} = P (A|..
Theorem 1:(Addition Rule of Probability)
If A and B are any two events, the..
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