With the information that is available from the question, it is impossible.
(A' ∩ B') = (A È B)'
In mathematics, a complement refers to the difference between a set and a subset of that set. For example, if ( A ) is a set and ( B ) is a subset of ( A ), the complement of ( B ) in ( A ) consists of all elements in ( A ) that are not in ( B ). This concept is commonly used in set theory and probability, where the complement of an event represents all outcomes not included in that event.
P(A given B)*P(B)=P(A and B), where event A is dependent on event B. Finding the probability of an independent event really depends on the situation (dart throwing, coin flipping, even Schrodinger's cat...).
In mathematics, specifically in set theory, the term "B complement" refers to the elements that are not in set B but are in a universal set U. It is denoted as ( B' ) or ( U - B ). This concept helps to define the difference between the universal set and a given subset, allowing for operations like union and intersection to be performed more easily. Essentially, B complement includes all the elements of the universal set that do not belong to set B.
the n partition of A , in B , so the results of summation of all Ai's probabilities which individually intersect with B divided by probability of B is totals theorem, so simply we say if you want to find the probability of any partition is bays theorem and if you have partitions and wants to find the probability of A is Totals theorem. (S.M SINDHI QUCEST LARKANA)
P(A given B')=[P(A)-P(AnB)]/[1-P(B)].
P(A given B')=[P(A)-P(AnB)]/[1-P(B)].In words: Probability of A given B compliment is equal to the Probability of A minus the Probability of A intersect B, divided by 1 minus the probability of B.
Prob(A given B) = Prob(A and B)/Prob(B)
If A and B are independent, then you can multiply the two probabilities
Define your event as [A occurs and B does not occur] or as [A occurs and B' occurs] where B' is the complement of B. Equivalently, this is the event that [A and B' both occur].
(A' ∩ B') = (A È B)'
The probability of event A occurring given event B has occurred is an example of conditional probability.
With probability ratios the value you get to describe the strength of the relationship when you compare (A given B) to (A given not B) is not the same as what you get when you compare (not A given B) to (not A given not B). This is, IMHO, a big problem. There is no such problem with odds ratios.
Given two events, A and B, the conditional probability rule states that P(A and B) = P(A given that B has occurred)*P(B) If A and B are independent, then the occurrence (or not) of B makes no difference to the probability of A happening. So that P(A given that B has occurred) = P(A) and therefore, you get P(A and B) = P(A)*P(B)
Given two events, A and B, the probability of A or B is the probability of occurrence of only A, or only B or both. In mathematical terms: Prob(A or B) = Prob(A) + Prob(B) - Prob(A and B).
Pr(A | B)
P(A'/B)=P(A'nB)/P(B)