Learning Outcomes
- Calculate the probability of a complementary event.
- Identify if events are mutually exclusive.
- Use the Addition Rule to compute the probability of events combined with “or”.
- Determine if events are independent.
- Use the Multiplication Rule to compute the probability of joint (simultaneous) events.
Recall operations on fractions
Adding and subtracting fractions with common denominators
[latex]\dfrac{a}{c}\pm \dfrac{b}{c}=\dfrac{a\pm b}{c}[/latex]
In the two equations below, note that this relationship is described in both directions.
That is, it is also true that
[latex]\dfrac{a\pm b}{c}=\dfrac{a}{c}\pm \dfrac{b}{c}[/latex]
The second equation furthermore includes the fact that
[latex]\dfrac{a}{a}=1[/latex]
Complementary Events
Now let us examine the probability that an event does not happen. As in the previous section, consider the situation of rolling a six-sided die and first compute the probability of rolling a six: the answer is P(six) =1/6. Now consider the probability that we do not roll a six: there are 5 outcomes that are not a six, so the answer is P(not a six) = [latex]\frac{5}{6}[/latex]. Notice that
[latex]P(\text{six})+P(\text{not a six})=\frac{1}{6}+\frac{5}{6}=\frac{6}{6}=1[/latex]
This is not a coincidence. Consider a generic situation with n possible outcomes and an event E that corresponds to m of these outcomes. Then the remaining n – m outcomes correspond to E not happening, thus
[latex]P(\text{not}E)=\frac{n-m}{n}=\frac{n}{n}-\frac{m}{n}=1-\frac{m}{n}=1-P(E)[/latex]
Complement of an Event
The complement of an event is the event “E doesn’t happen”
- The notation [latex]\bar{E}[/latex] is used for the complement of event E.
- We can compute the probability of the complement using [latex]P\left({\bar{E}}\right)=1-P(E)[/latex]
- Notice also that [latex]P(E)=1-P\left({\bar{E}}\right)[/latex]
example
If you pull a random card from a deck of playing cards, what is the probability it is not a heart?
This situation is explained in the following video.
Try It
Probability of either of two events occurring
example
Suppose we flipped a coin and rolled a die, and wanted to know the probability of getting a head on the coin or a 6 on the die.
ADDITION RULE OF PROBABILITY: P(A or B)
The probability of either A or B occurring (or both) is
[latex]P(A\text{ or }B)=P(A)+P(B)–P(A\text{ and }B)[/latex]
example
Suppose we draw one card from a standard deck. What is the probability that we get a Queen or a King?
See more about this example and the previous one in the following video.
In the last example, the events were mutually exclusive (cannot happen at the same time), so P(A or B) = P(A) + P(B).
Mutually Exclusive Events
Events A and B are mutually exclusive events if Event B and Event A cannot occur at the same time.
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example
Suppose we draw one card from a standard deck. What is the probability that we get a red card or a King?
Try It
In your drawer you have 10 pairs of socks, 6 of which are white, and 7 tee shirts, 3 of which are white. If you reach in and randomly grab a pair of socks and a tee shirt, what is the probability at least one is white?
Probability of two events occurring simultaneously
The previous examples looked at the probability of either event occurring. Now we will look at the probability of both events occurring.
example
Suppose we flipped a coin and rolled a die, and wanted to know the probability of getting a head on the coin and a 6 on the die.
The prior example contained two independent events. Getting a certain outcome from rolling a die had no influence on the outcome from flipping the coin.
Independent Events
Events A and B are independent events if the probability of Event B occurring is the same whether or not Event A occurs.
example
Are these events independent?
- A fair coin is tossed two times. The two events are (1) first toss is a head and (2) second toss is a head.
- The two events (1) “It will rain tomorrow in Houston” and (2) “It will rain tomorrow in Galveston” (a city near Houston).
- You draw a card from a deck, then draw a second card without replacing the first.
When two events are independent, the probability of both occurring is the product of the probabilities of the individual events.
recall multiplying fractions
To multiply fractions, place the product of the numerators over the product of the denominators.
[latex]\dfrac{a}{b} \cdot \dfrac{c}{d} = \dfrac{ac}{bd}[/latex]
MULTIPLICATION RULE OF PROBABILITY: P(A and B) for independent events
If events A and B are independent, then the probability of both A and B occurring is
[latex]P\left(A\text{ and }B\right)=P\left(A\right)\cdot{P}\left(B\right)[/latex]
where P(A and B) is the probability of events A and B both occurring, P(A) is the probability of event A occurring, and P(B) is the probability of event B occurring
If you look back at the coin and die example from earlier, you can see how the number of outcomes of the first event multiplied by the number of outcomes in the second event multiplied to equal the total number of possible outcomes in the combined event.
Recall fraction reduction
To write a fraction in reduced terms, first take the prime factorization of the numerator and denominator, then cancel out factors that are common in the numerator and the denominator.
Ex. [latex]\dfrac{12}{18}=\dfrac{\cancel{2}\cdot 2\cdot \cancel{3}}{\cancel{2}\cdot 3\cdot \cancel{3}}=\dfrac{2}{3}[/latex]
example
In your drawer you have 10 pairs of socks, 6 of which are white, and 7 tee shirts, 3 of which are white. If you randomly reach in and pull out a pair of socks and a tee shirt, what is the probability both are white?
Examples of joint probabilities are discussed in this video.
Try It
Example
The table below shows the number of survey subjects who have received and not received a speeding ticket in the last year, and the color of their car. Find the probability that a randomly chosen person:
- Has a red car and got a speeding ticket
- Has a red car or got a speeding ticket.
| Speeding ticket | No speeding ticket | Total | |
| Red car | 15 | 135 | 150 |
| Not red car | 45 | 470 | 515 |
| Total | 60 | 605 | 665 |
This table example is detailed in the following explanatory video.
Try It
Now, let’s consider the situation where the events are not independent. When two events are dependent, the probability of both occurring is the product of the first event happening and the second event happening assuming the first one happened.
For example, if you draw a card from a deck, then the sample space for the next card drawn has changed, because you are now working with a deck of 51 cards. In the following example we will show you how the computations for events like this are different from the computations we did for independent events.
example
What is the probability that two cards drawn at random from a deck of playing cards will both be aces?
MULTIPLICATION RULE OF PROBABILITY: P(A and B) for dependent events
If Events A and B are not independent, then P(A and B) = P(A) · P(B | A)
Converting a fraction to decimal form
Probabilities can be expressed in fraction or decimal form. To convert a fraction to a decimal, use a calculator to divide the numerator by the denominator.
Ex. [latex]\dfrac{19}{51}=19 \div 51 \approx 0.3725[/latex]
example
If you pull 2 cards out of a deck, what is the probability that both are spades?
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Example
If you draw two cards from a deck, what is the probability that you will get the Ace of Diamonds and a black card?
These two playing card scenarios are discussed further in the following video.
Try It
Candela Citations
- Revisoin and Adaptation. Provided by: Lumen Learning. License: CC BY: Attribution
- Working With Events. Authored by: David Lippman. Located at: http://www.opentextbookstore.com/mathinsociety/. Project: Math in Society. License: CC BY-SA: Attribution-ShareAlike
- ace-playing-cards-deck-spades. Authored by: PDPics. Located at: https://pixabay.com/en/ace-playing-cards-deck-spades-167052/. License: CC0: No Rights Reserved
- Probability - Complements. Authored by: OCLPhase2's channel. Located at: https://youtu.be/RnljiW6ZM6A. License: CC BY: Attribution
- Probability of two events: P(A or B). Authored by: OCLPhase2's channel. Located at: https://youtu.be/klbPZeH1np4. License: CC BY: Attribution
- Joint probabilities of independent events: P(A and B). Authored by: OCLPhase2's channel. Located at: https://youtu.be/6F17WLp-EL8. License: CC BY: Attribution
- Probabilities from a table: AND and OR. Authored by: OCLPhase2's channel. Located at: https://youtu.be/HWrGoM1yRaU. License: CC BY: Attribution
- Basic conditional probability. Authored by: OCLPhase2's channel. Located at: https://youtu.be/b6tstekMlb8. License: CC BY: Attribution
- Conditional probability with cards. Authored by: OCLPhase2's channel. Located at: https://youtu.be/ngyGsgV4_0U. License: CC BY: Attribution
- Conditional probability from a table. Authored by: OCLPhase2's channel. Located at: https://youtu.be/LH0cuHS9Ez0. License: CC BY: Attribution
- Question ID 7111, 7113, 7114, 7115. Authored by: unknown. License: CC BY: Attribution. License Terms: IMathAS Community License CC-BY + GPL
