Initially, probability was a branch of
Probability theory is the branch of Mathematics concerned with analysis of random phenomena.
Two broad divisions of probability are
Subjective probability may be used in
An experiment is known to be random if the results of the experiment
An event that can be split into further events is known as
Which of the following pairs of events are mutually exclusive?
If P(A) = P(B), then
If P(A ∩ B) = 0, then the two events A and B are
If for two events A and B, P(AUB) = 1, then A and B are
If an unbiased coin is tossed once, then the two events Head and Tail are
If P(A) = P(B), then the two events A and B are
If for two events A and B, P(A ∩ B) ≠ P(A) × P(B), then the two events A and B are
If P(A/B) = P(A), then
If two events A and B are independent, then
If two events A and B are independent, then
If two events A and B are mutually exclusive, then
If a coin is tossed twice, then the events 'occurrence of one head', 'occurrence of 2 heads' and 'occurrence of no head' are
The probability of an event can assume any value between
If P(A) = 0, then the event A
If P(A) = 1, then the event A is known as
If p : q are the odds in favour of an event, then the probability of that event is
If P(A) = 5/9, then the odds against the event A is
If A, B and C are mutually exclusive and exhaustive events, then P(A) + P(B) + P(C) equals to
If A denotes that a student reads in a school and B denotes that he plays cricket, then
P(B/A) is defined only when
P(A/B') is defined only when
For two events A and B, P(A ∪ B) = P(A) + P(A) only when
Addition Theorem of Probability states that for any two events A and B,
For any two events A and B,
For any two events A and B,
The limitations of the classical definition of probability
According to the statistical definition of probability, the probability of an event A is the
The Theorem of Compound Probability states that for any two events A and B.
Correct Answer : C
Explanation : If two events, A and B, are mutually exclusive, then the probability that either A or B occurs is the sum of their probabilities.
For mutually inclusive events, P (A or B) = P(A) + P(B)  P(A and B).
If A and B are mutually exclusive events, then
If P(A–B) = P(B–A), then the two events A and B satisfy the condition
The number of conditions to be satisfied by three events A, B and C for independence is
If two events A and B are independent, then P(A ∩ B)
Values of a random variable are
Expected value of a random variable
If all the values taken by a random variable are equal then
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