Bayes Theorem, Binomial and Poisson Distributions
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 publishe..
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 publishe..Binomial Distribution
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 = "pro..
Theorem:
The number of circular permutations of n different objects is (n-1)..
Theorem:
The number of permutations of n dissimilar things taken r ..
The number of permutations of n dissimilar things taken r ..Theorems of Probability
Theorem 1:(Addition Rule of Probability) - If A and B are any two events, th..
Theorem 1:(Addition Rule of Probability) - If A and B are any two events, th..Baye's Theorem
Baye's Theorem - In the previous section, we have learnt that i) If A and B are two mutually exclusive events, then ii) Before we state and prove Baye's Theorem, we use the above two rules to state the law of total probability. The law of total probability is..
Baye's Theorem - In the previous section, we have learnt that i) If A and B are two mutually exclusive events, then ii) Before we state and prove Baye's Theorem, we use the above two rules to state the law of total probability. The law of total probability is..Baye's 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 S. Baye's Theorem: Let S be a sample space. If A 1 , A, A 3 ... A n are mutually exclusive and exhaustive ev..
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 S. Baye's Theorem: Let S be a sample space. If A 1 , A, A 3 ... A n are mutually exclusive and exhaustive ev..Baye's Theorem Let S be a sample space. If A 1 , A, A 3 ... A n are mutually exclusive and exhaustive events such that P(A i ) 0 for all i. Then for any event A which is a subset of We hav..
Let S be a sample space. If A 1 , A, A 3 ... A n are mutually exclusive and exhaustive events such that P(A i ) 0 for all i. Then for any event A which is a subset of We hav..Poisson Distribution as a Limiting Form of the Binomial Distribution
>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 ..
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 ..
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 ..See what our Users say :
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