Probability (continued)
Let A and B be any two events associated with a random experiment. The probability of occurrence of event A when the event B has already occurred is called the conditional probability of A when B is given and is denoted as P(A/B..
Conditional Probability
Conditional Probability - Let us consider the random experiment of throwing a die. Let A be the event of getting an odd number on the die. \ S = {1, 2, 3, 4, 5, 6} and A = {1, 3, 5} Let B = {2, 3, 4, 5, 6}. If, after the die is thrown, we are given the information, that the event B has oc..
Conditional Probability - Let us consider the random experiment of throwing a die. Let A be the event of getting an odd number on the die. \ S = {1, 2, 3, 4, 5, 6} and A = {1, 3, 5} Let B = {2, 3, 4, 5, 6}. If, after the die is thrown, we are given the information, that the event B has oc..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 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..Independent Experiment
Two random experiments are said to be independent if for every pair of events E and F, where E is associated with the first experiment and F is associated with the second experiment, the probability of simultaneous occurrence of E and F, when the two experiments are performed, ..
Two random experiments are said to be independent if for every pair of events E and F, where E is associated with the first experiment and F is associated with the second experiment, the probability of simultaneous occurrence of E and F, when the two experiments are performed, ..Probability of an Event
Probability of an Event - So far, we have introduced the sample of an experiment and used it to describe events. In this section, we introduce probabilities associated to the events. If a trial results in n-exhaustive, mutually exclusive and equally likely cases and m of them ar..
Probability of an Event - So far, we have introduced the sample of an experiment and used it to describe events. In this section, we introduce probabilities associated to the events. If a trial results in n-exhaustive, mutually exclusive and equally likely cases and m of them ar..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 expl..
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 expl..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 wh..
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 wh..Equally Likely Outcomes
The outcomes of a random experiment are said to be equally likely, if each one of them has equal chance of occurrence. Example: The outcomes of an unbiased coin are equally like..
Probability - I Summary
: All the outcomes of a random experiment. Probability of an event: P(A) P(A C ) = Probability of the non-occurrence of A = 1- P(A) Addition Theorem: If A and B are any two events of a random If A, B, C are there events of a random experiment th..
: All the outcomes of a random experiment. Probability of an event: P(A) P(A C ) = Probability of the non-occurrence of A = 1- P(A) Addition Theorem: If A and B are any two events of a random If A, B, C are there events of a random experiment th..Note 4:
If m is the number of cases favourable to A. Then m - n is favourable to "non occurrence of A"..
If m is the number of cases favourable to A. Then m - n is favourable to "non occurrence of A"..See what our Users say :
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