Q. The previous probabilities in Bayes Theorem that are changed with the help of new available information are classified as

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Q. The conditional probability of two events Y and Z written as P(Z|Y) = P(Y and Z) ⁄ P(A) shows that the events are

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Q. If in an experiment the A and B are two events, then the occurrence of event A or B simultaneously is represented by

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Q. If the number of outcomes in collection are 2 and the distinct outcomes are 4 then the count value according to permutations is

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Q. The payments received by cheques or cash is an example of

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Q. If two events G and H are classified as joint events then the events are represented as

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Q. Considering the events Y and Z, the occurrence of Z and the non-occurrence of Y is represented by

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Q. The number of favorable occurrences are divided by the total number of possible occurrences to calculate

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Q. The sample space for the experiment in which two coins are tossed is

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Q. The type of probability approach in which the event A is the ratio explaining the number of times event A is occurred in experiments is classified as

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Q. If the occurrence of a statistical event A does not affect the occurrence of event B and vice versa then these events are classified as

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Q. If the occurrence of one event does not affects or explains the occurrence of other event then the events are classified as

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Q. If the factory has four machines, machines will be completely depreciated in next year and the chances of failure of all machines respectively are 0.24, 0.45, 0.35, 0.38 then the probability of failure of all machines before next year is

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Q. If the occurrence of one event affects or explains the occurrence of other event then the events are classified as

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