Probability Addition Rule and Conditional

When two events, A and B, are mutually exclusive, the probability that A or B will occur is the sum of the probability of each event. ... The probability that A or B will occur is the sum of the probability of each event, minus the probability of the overlap. P(A or B).....is called the ...

• general addition rule

• general multiplication rule

• general compound rule

• general marginal rule

two sets is a new set that contains all of the elements that are in at least one of the two sets.

• Intersection

• Union

• Sample Space

• Complement

The __________ of events A and B, denoted A∩B is the collection of all outcomes that are elements of both of the sets A and B. It corresponds to combining descriptions of the two events using the word “and.”

• Union

• Intersection

• Independence

• Mutually Exclusive

states the probability of two events is the sum of the probability that either will happen minus the probability that both will happen.

• Conditional Probability

• Independence

• Addition Rule

• Mutually Exclusive

________is the probability of one event occurring with some relationship to one or more other events

• Independence

• Addition Rule

• Union

• Conditional Probability

If the occurrence of one does not affect the probability of occurrence of the other

• Independence

• Sample Space

• Dependent

• Intersection

What is the branch of mathematics that describes the patterns of chance outcomes?

• Algebra

• Geometry

• Probability

• Calculus

What is the formula for the General Addition Rule in probability?

• P(A or B) = P(A) + P(B) - P(A and B)

• P(A or B) = P(A) + P(B)

• P(A or B) = P(A) - P(B)

• P(A or B) = P(A) * P(B)

What is the purpose of tree diagrams in probability?

• To calculate the mean of a data set

• To organize circumstances and outcomes in conditional probability

• To determine the mode of a data set

• To find the median of a data set

When are two events considered independent?

• When P(A and B) = P(A) + P(B)

• When P(A|B) = P(A) and P(B|A) = P(B)

• When P(A) = P(B)

• When P(A|B) = P(B) and P(B|A) = P(A)