13.Probability Quiz

What is the conditional probability of an event E, given the occurrence of the event F?

• P(E|F) = P(E∩F) / P(E), P(E) ≠ 0

• P(E|F) = P(E∩F) / P(F), P(F) ≠ 0

• P(E|F) = P(E∩F) / P(F)

• P(E|F) = P(E∩F) / P(E)

What is the range of conditional probability P(E|F)?

• 0 ≤ P(E|F) ≤ 100

• 1 ≤ P(E|F) ≤ 10

• 1 ≤ P(E|F) ≤ 100

• 0 ≤ P(E|F) ≤ 1

What is the probability of the complement of event E, given the occurrence of the event F?

• P(E’|F) = P(E|F) - 1

• P(E’|F) = 1 + P(E|F)

• P(E’|F) = 1 - P(E|F)

• P(E’|F) = P(E|F) + 1

What is the formula for P((E∪F)|G)?

• P((E∪F)|G) = P(E|G) + P(F|G) + P((E∩F)|G)

• P((E∪F)|G) = P(E|G) + P(F|G) - P((E∩F)|G)

• P((E∪F)|G) = P(E|G) - P(F|G) + P((E∩F)|G)

• P((E∪F)|G) = P(E|G) - P(F|G) - P((E∩F)|G)

What is the formula for P(E∩F) when P(E) ≠ 0?

• P(E∩F) = P(E) / P(F|E)

• P(E∩F) = P(E) P(F|E)

• P(E∩F) = P(E) + P(F|E)

• P(E∩F) = P(E) - P(F|E)

What is the formula for P(E∩F) when P(F) ≠ 0?

• P(E∩F) = P(F) P(E|F)

• P(E∩F) = P(F) - P(E|F)

• P(E∩F) = P(F) / P(E|F)

• P(E∩F) = P(F) + P(E|F)

If E and F are independent, what is the value of P(E∩F)?

• P(E∩F) = P(E) + P(F)

• P(E∩F) = P(E) - P(F)

• P(E∩F) = P(E) P(F)

• P(E∩F) = P(E) / P(F)

If E and F are independent, what is the value of P(E|F)?

• P(E|F) = P(E)

• P(E|F) = P(F)

• P(E|F) = P(E) + P(F)

• P(E|F) = P(E) - P(F)

What is Baye’s Theorem used for?

• Finding the probability of an event given another related event has occurred

• Finding the probability of an event without any related event

• Finding the probability of an event without any condition

• Finding the probability of an event without any prior knowledge

What is the formula for Baye’s Theorem?

• P(Ei|A) = P(Ei) P(A|Ei) / ∑(P(Ej) P(A|Ej))

• P(Ei|A) = P(Ei) P(A|Ei) / ∑(P(Ej) P(A|Ej)), j=1 to n

• P(Ei|A) = P(Ei) P(A|Ei) / ∑(P(Ej) P(A|Ej)), j=1 to n-1

• P(Ei|A) = P(Ei) P(A|Ei) / ∑(P(Ej) P(A|Ej)), j=0 to n