Introduction To Probability
The previous probabilities in Bayes Theorem that are changed with the help of new available information are classified as
independent probabilities
posterior probabilities
interior probabilities
dependent probabilities
posterior probabilities
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For two events, the probability of occurrence of both events at same time or occurrence in series is classified asA. joint probability
B. dependent probability
C. series probability
D. conditional probability
In a Venn diagram used to represent probabilities, the occurred events are represented by
A. circle
B. rectangle
C. square
D. triangle
The difference between sample space and subset of sample space is considered as
A. numerical complementary events
B. equal compulsory events
C. complementary events
D. compulsory events
The probability of second event in the situation if the first event has been occurred is classified as
A. series probability
B. conditional probability
C. joint probability
D. dependent probability
Consider an event B, the non-occurrence of event B is represented by
A. union of A
B. complement of A
C. intersection of A
D. A is equal to zero
The events in which some points of sample are common are considered as
A. divisional events
B. overlapping events
C. common events
D. additive events
The variation in which outcomes of experiments are effected by uncontrolled factors is considered as
A. random variation
B. mesokurtic variation
C. platykurtic variation
D. mesokurtic variation
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