Addition Rule and Rule of Complements
Compound Events and the General Addition Rule
- A compound event combines two or more events.
- The event A or B occurs if A occurs, B occurs, or both occur.
- The general addition rule computes probabilities of events in the form A or B.
General Addition Rule
- For any two events A and B, the probability of A or B is:
P(A \text{ or } B) = P(A) + P(B) - P(A \text{ and } B)
Example
- 1,000 adults were asked about favoring a law for higher education support and their likelihood to vote.
- Classified as "likely to vote" or "not likely to vote."
Data:
- Likely to vote: 372
- Favor the law: 151
- Both likely to vote and favor the law: 20
- Only likely to vote: 262
- Only Favor the law: 87
Calculations:
- Probability of likely to vote:
- Total people likely to vote = 372 + 262 + 87 = 721
- P(\text{likely to vote}) = \frac{721}{1000} = 0.721
- Probability of favoring the law:
- Total people who favor the law = 372 + 151 = 523
- P(\text{favors the law}) = \frac{523}{1000} = 0.523
- Probability of both likely to vote and favoring the law:
- P(\text{likely to vote and favors the law}) = \frac{372}{1000} = 0.372
- Using the general addition rule:
- P(\text{likely to vote or favors the law}) = P(\text{likely to vote}) + P(\text{favors the law}) - P(\text{likely to vote and favors the law})
- P(\text{likely to vote or favors the law}) = 0.721 + 0.523 - 0.372 = 0.872
Mutually Exclusive Events
- Two events are mutually exclusive if it is impossible for both events to occur simultaneously.
Examples
- Rolling a die:
- Event A: Die comes up as 3.
- Event B: Die comes up as an even number.
- These are mutually exclusive because the die cannot be both 3 and an even number at the same time.
- Tossing a coin twice:
- Event A: One of the tosses is heads.
- Event B: One of the tosses is tails.
- These are NOT mutually exclusive because it's possible to get heads, tails or tails, heads.
- If events A and B are mutually exclusive, then P(A \text{ and } B) = 0
- Simplified general addition rule:
- P(A \text{ or } B) = P(A) + P(B)
Example
- Olympics example with 10,735 athletes.
- 530 from the US
- 277 from Canada
- 102 from Mexico
- What is the probability that an athlete chosen at random represents the US or Canada?
Solution:
- Events are mutually exclusive (cannot compete for both US and Canada).
- P(\text{US or Canada}) = P(\text{US}) + P(\text{Canada})
- P(\text{US or Canada}) = \frac{530}{10735} + \frac{277}{10735} = \frac{807}{10735} \approx 0.07517
Complements
- The complement of an event A is the event that A does not occur, denoted as A^C
- Example: If there is a 60% chance of rain, there is a 40% chance it will not rain.
Examples: Statistics Class
- 200 students enrolled.
- Event: Exactly 50 are business majors.
- Complement: The number of business majors is not 50.
- Event: More than 50 are business majors.
- Complement: 50 or fewer are business majors.
- Event: At least 50 of them are business majors.
- Complement: Fewer than 50 are business majors.
Rule of Complements
- P(A^C) = 1 - P(A)
- Example: Wall Street Journal reports 40% of cars sold were small cars.
- Probability that a randomly chosen car is not a small car:
- P(\text{not a small car}) = 1 - P(\text{small car}) = 1 - 0.4 = 0.6 or 60%.
Application Example: Foundry Manufacturing
- 500 cast aluminum parts manufactured.
- Some with major flaws.
- Some with minor flaws.
- Some with both.
Table Results:
- Major flaw only = 35
- Minor flaw only = 75
- Both major and minor flaws = 20
- No flaw = 370
Probability Calculations:
- A. Probability of a major flaw:
- Total with major flaw = 20 + 35 = 55
- P(\text{major flaw}) = \frac{55}{500} = 0.11
- B. Probability of a minor flaw:
- Total with minor flaw = 20 + 75 = 95
- P(\text{minor flaw}) = \frac{95}{500} = 0.19
- C. Probability of a major or minor flaw:
- Using the general addition rule:
- P(\text{major flaw or minor flaw}) = P(\text{major flaw}) + P(\text{minor flaw}) - P(\text{major flaw and minor flaw})
- P(\text{major flaw and minor flaw}) = \frac{20}{500} = 0.04
- P(\text{major flaw or minor flaw}) = 0.11 + 0.19 - 0.04 = 0.26
- D. Probability of no major flaw:
- Using the complement rule:
- P(\text{no major flaw}) = 1 - P(\text{major flaw}) = 1 - 0.11 = 0.89