A probability law used to compute the probability of the union of two events. It is P(a ∙ B) = P(a) + P(B) − P(a ∩ B). For mutually exclusive events, P(a ∩ B) = 0; in this case the addition law reduces to P(a ∙ B) = P(a) + P(B).
Stats 2 Exam

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Jeffrey Worth
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37 questions
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1.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
Addition Law
Bayes Theorem
Classical Method
Conditional Probability
2.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
Two requirements that restrict the man- ner in which probability assignments can be made: (1) for each experimental outcome Ei we must have 0 ≤ P(Ei) ≤ 1; (2) considering all experimental outcomes, we must have P(E1) + P(E2) + . . . + P(En) = 1.0.
Multiplication Law
Combination
Basic requirements for assigning probabilities
Mutually Exclusive Events
3.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
A method used to compute posterior probabilities.
Joint Probability
Bayes’ theorem
marginal Probability
Multiplication Law
4.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
A method of assigning probabilities that is appropriate when all the experimental outcomes are equally likely.
Independent Events
Combination
Multi-step Experiment
Classical method
5.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
In an experiment we may be interested in determining the number of ways n objects may be selected from among n objects without regard to the order in which the n objects are selected.
Complement of A
Conditional Probability
Combination
Intersection of A & B
6.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
The event consisting of all sample points that are not in a.
Complement of A
Event
Independent Events
Intersection of A & B
7.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
The probability of an event given that another event already occurred. The conditional probability of a given B is P(a ∣ B) = P(a ∩ B)/P(B
Conditional probability
Marginal probability
Joint probability
Multiplication law
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