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Multiplication Rule

Multiplication Rule

A method for finding the probability that both of two events occur.

 

Multiplication Rule: If A and B are independent, P(A and B)=P(A)P(B). Otherwise, P(A and B)=P(A)P(B|A).


Example: P(rolling 1 on both rolls) = P(A and B) = P(A)P(B) = 1/6 · 1/6 = 1/36
Example using Multiplication Rule: bag with 3 red, 3 black balls. P(A)=1/2, P(B|A)=2/5, P(A and B)=1/5.

 

See also

Independent events, addition rule, conditional probability

Key Formula

P(A and B)=P(A)P(BA)P(A \text{ and } B) = P(A) \cdot P(B \mid A)
Where:
  • P(A and B)P(A \text{ and } B) = The probability that both event A and event B occur
  • P(A)P(A) = The probability that event A occurs
  • P(BA)P(B \mid A) = The conditional probability that event B occurs given that event A has already occurred

Worked Example

Problem: A bag contains 5 red marbles and 3 blue marbles. You draw two marbles without replacement. What is the probability that both marbles are red?
Step 1: Identify event A and event B. Let A = first marble is red, and B = second marble is red.
Step 2: Find the probability that the first marble is red. There are 5 red marbles out of 8 total.
P(A)=58P(A) = \frac{5}{8}
Step 3: Find the conditional probability that the second marble is red, given the first was red. After removing one red marble, 4 red marbles remain out of 7 total.
P(BA)=47P(B \mid A) = \frac{4}{7}
Step 4: Apply the multiplication rule by multiplying the two probabilities.
P(A and B)=5847=2056=514P(A \text{ and } B) = \frac{5}{8} \cdot \frac{4}{7} = \frac{20}{56} = \frac{5}{14}
Answer: The probability of drawing two red marbles is 5140.357\frac{5}{14} \approx 0.357.

Another Example

This example uses independent events, so the formula simplifies to P(A) · P(B) without needing conditional probability. The first example involved dependent events (drawing without replacement), where the conditional probability was essential.

Problem: You roll a fair six-sided die and flip a fair coin. What is the probability of rolling a 3 and getting heads?
Step 1: Identify the events. Let A = rolling a 3, and B = getting heads. Since the die roll and coin flip do not affect each other, these events are independent.
Step 2: Find each individual probability.
P(A)=16,P(B)=12P(A) = \frac{1}{6}, \quad P(B) = \frac{1}{2}
Step 3: Because the events are independent, P(BA)=P(B)P(B \mid A) = P(B). The multiplication rule simplifies to:
P(A and B)=P(A)P(B)=1612=112P(A \text{ and } B) = P(A) \cdot P(B) = \frac{1}{6} \cdot \frac{1}{2} = \frac{1}{12}
Answer: The probability of rolling a 3 and getting heads is 1120.083\frac{1}{12} \approx 0.083.

Frequently Asked Questions

What is the difference between the multiplication rule for independent and dependent events?
For independent events, the occurrence of one event does not change the probability of the other, so the rule simplifies to P(A and B)=P(A)P(B)P(A \text{ and } B) = P(A) \cdot P(B). For dependent events, the second probability changes based on the first event's outcome, so you must use the full formula P(A and B)=P(A)P(BA)P(A \text{ and } B) = P(A) \cdot P(B \mid A). The independent version is actually a special case of the general rule, since P(BA)=P(B)P(B \mid A) = P(B) when events are independent.
When do you use the multiplication rule vs the addition rule?
Use the multiplication rule when you want the probability that both events occur (A and B). Use the addition rule when you want the probability that at least one of the events occurs (A or B). A helpful way to remember: "and" means multiply, "or" means add (with an adjustment for overlap).
Can the multiplication rule be extended to more than two events?
Yes. For three events A, B, and C, the rule extends to P(A and B and C)=P(A)P(BA)P(CA and B)P(A \text{ and } B \text{ and } C) = P(A) \cdot P(B \mid A) \cdot P(C \mid A \text{ and } B). Each successive probability is conditioned on all the previous events having occurred. If all events are independent, this simplifies to P(A)P(B)P(C)P(A) \cdot P(B) \cdot P(C).

Multiplication Rule vs. Addition Rule

Multiplication RuleAddition Rule
Question it answersWhat is the probability that A and B both occur?What is the probability that A or B (or both) occurs?
General formulaP(A and B) = P(A) · P(B | A)P(A or B) = P(A) + P(B) − P(A and B)
Simplified caseP(A) · P(B) when events are independentP(A) + P(B) when events are mutually exclusive
Key word clue"and", "both", "all""or", "either", "at least one"
Result compared to individual probabilitiesAlways ≤ the smaller individual probabilityAlways ≥ the larger individual probability (for positive probabilities)

Why It Matters

The multiplication rule appears throughout statistics courses, from basic probability problems to more advanced topics like Bayes' theorem and probability distributions. You will use it whenever a problem asks for the likelihood that multiple conditions are all satisfied — for example, passing both a written test and a practical exam, or drawing a specific sequence of cards. Understanding when events are independent versus dependent is a critical skill tested on the AP Statistics exam and standardized tests like the SAT and ACT.

Common Mistakes

Mistake: Multiplying individual probabilities without adjusting for dependence.
Correction: When events are dependent (such as drawing cards without replacement), the probability of the second event changes after the first event occurs. Always check whether you need to use P(B | A) rather than P(B). For example, drawing two aces from a deck without replacement uses P(B | A) = 3/51, not 4/52.
Mistake: Using the multiplication rule when the problem asks for "or" instead of "and".
Correction: The multiplication rule finds P(A and B). If a problem asks for the probability of A or B occurring, you need the addition rule: P(A or B) = P(A) + P(B) − P(A and B). Read the problem carefully for keywords like "both" (multiply) versus "either" (add).

Related Terms

  • ProbabilityThe foundational concept the multiplication rule applies to
  • EventAn outcome or set of outcomes whose probability is calculated
  • Independent EventsEvents where the simplified multiplication rule applies
  • Addition RuleCounterpart rule for finding P(A or B)
  • Conditional ProbabilityP(B | A), a key component of the general formula
  • Bayes' TheoremDerived from the multiplication rule to update probabilities
  • Sample SpaceThe set of all possible outcomes underlying probability calculations