This is, also, otherwise called as unconditional probability which refers to the probability of occurrence of an event without waiting for the occurrence of another event.
The marginal probability of the events, say, A and B are represented as follows:. In a joint probability table, the marginal probability of an event can be easily calculated by adding the two joint probabilities relating to an event both row and column-wise. It is to be noted that sum of the marginal probabilities of all the related events will be equal to one. All these have been shown in the joint probability tables as solution to the illustrations 19 and 20 above.
Interrelationship between the Conditional, Joint and Marginal Probabilities: All the three Conditional, Joint, and Marginal probabilities are inter-related with each other which can be seen from the following model:. This probability is known is known is different names, viz. This has been introduced by Thomas Bayes an English mathematician in his work known as Bayesian Decision Theory published in This theory consists of finding the probability of an event by taking into account of a given a sample information.
Thus, a sample of 3 defective items out of event A might be used to estimate the probability that a machine is not working properly event B. It is to be noted that the Bayesian Probability is based on the formula of conditional probability where, A1 and A2 are two events which are mutually exclusive and exhaustive, and B is a simple event which intersects each of the A events as shown in the following Venn diagram.
This is called posterior probability because; it is calculated after information is taken into account. This is called revised probability as it is determined by revising the prior probabilities in the light of the additional information gathered. Further, this called inverse probability also, as it consists of finding the probability of a probability.
However, the Bayesian, or the Posterior probabilities are always conditional probabilities which are calculated for every events as follows:. Joint probability is the product of prior probability of an event of A and conditional probability of another event B, i.
There are different types of probability which are briefly identified here as under: The value of such a probability is calculated by the following simple formula: The formula of computing such probability is as follows: It is to be noted that where conditional probability is attached to the two independent events say A and B, the conditional probabilities of A and B will be represented thus: The marginal probability of the events, say, A and B are represented as follows: All the three Conditional, Joint, and Marginal probabilities are inter-related with each other which can be seen from the following model: We offer advantages, which not every homework service could give to their customers.
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Probability refers to ‘an event’ the happing and non-happening of which is uncertain, or contingent. Literally, it means a chance, a possibility, likelihood, or an odd. We provide probability homework help.
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