Chapter 4 T/F

Joint probability of two independent events A and B equals the sum of the individual probabilities of A and B.

False

Events are exhaustive if they do not share common outcomes of a sample space.

False

For two independent events A and B, the probability of their intersection is zero.

False

The complement of an event A, denoted by AC, within the sample space S, is the event consisting of all outcomes of A that are not in S.

False

The probability of a union of events can be greater than 1.

False

The total probability rule is defined as P(A) = P(A ∩ ∩ B) P(A ∩ ∩ B c Bc )

False

Bayes' theorem is used to update prior probabilities based on the arrival of new relevant information.

True

Mutually exclusive and collectively exhaustive events contain all outcomes of a sample space, and they do not share any common outcomes.

True

The intersection of two events A and B, denoted by A ∩ ∩ B, is the event consisting of all outcomes that are in A and B.

True

Subjective probability is assigned to an event by drawing on logical analysis.

False