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In a town, the attendance at a football game depends on the weather. On a sunny day the attendance is 60,000, on a cold day the attendance is 40,000, and on a stormy day the attendance is 30,000. If for the next football season, the weatherman has predicted that 30% of the days will be sunny, 50% of the days will be cold, and 20% days will be stormy, what is the expected attendance for a single game?

Using the expected value formula, we get

e = 60 , 000 . 30 + 40 , 000 . 50 + 30 , 000 . 20 = 44 , 000 size 12{e= left ("60","000" right ) left ( "." "30" right )+ left ("40","000" right ) left ( "." "50" right )+ left ("30","000" right ) left ( "." "20" right )="44","000"} {} .
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A lottery consists of choosing 6 numbers from a total of 51 numbers. The person who matches all six numbers wins $2 million. If the lottery ticket costs $1, what is the expected payoff?

Since there are 51 C6 = 18 , 009 , 460 size 12{"51"C6="18","009","460"} {} combinations of six numbers from a total of 51 numbers, the chance of choosing the winning number is 1 out of 18,009,460. So the expected payoff is

E = $ 2 million 1 18009460 $ 1 = $ 0 . 89 size 12{E= left ($2" million" right ) left ( { {1} over {"18009460"} } right ) - $1=$0 "." "89"} {}

This means that every time a person spends $1 to buy a ticket, he or she can expect to lose 89 cents.

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Probability using tree diagrams

As we have already seen, tree diagrams play an important role in solving probability problems. A tree diagram helps us not only visualize, but also list all possible outcomes in a systematic fashion. Furthermore, when we list various outcomes of an experiment and their corresponding probabilities on a tree diagram, we gain a better understanding of when probabilities are multiplied and when they are added. The meanings of the words and and or become clear when we learn to multiply probabilities horizontally across branches, and add probabilities vertically down the tree.

Although tree diagrams are not practical in situations where the possible outcomes become large, they are a significant tool in breaking the problem down in a schematic way. We consider some examples that may seem difficult at first, but with the help of a tree diagram, they can easily be solved.

A person has four keys and only one key fits to the lock of a door. What is the probability that the locked door can be unlocked in at most three tries?

Let U size 12{U} {} be the event that the door has been unlocked and L size 12{L} {} be the event that the door has not been unlocked. We illustrate with a tree diagram.

The Tree diagram shows the probability that the door will be unlocked on the first, second, and third try.
The probability of unlocking the door in the first try = 1/4 size 12{"The probability of unlocking the door in the first try"="1/4"} {}
The probability of unlocking the door in the second try = 3 / 4 1 / 3 = 1 / 4 size 12{"The probability of unlocking the door in the second try "= left (3/4 right ) left (1/3 right )=1/4} {}
The probability of unlocking the door in the third try = 3 / 4 2 / 3 1 / 2 = 1 / 4 size 12{"The probability of unlocking the door in the third try"= left (3/4 right ) left (2/3 right ) left (1/2 right )=1/4} {}

Therefore, the probability of unlocking the door in at most three tries = 1 / 4 + 1 / 4 + 1 / 4 = 3 / 4 size 12{"the probability of unlocking the door in at most three tries"=1/4+1/4+1/4=3/4} {}

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A jar contains 3 black and 2 white marbles. We continue to draw marbles one at a time until two black marbles are drawn. If a white marble is drawn, the outcome is recorded and the marble is put back in the jar before drawing the next marble. What is the probability that we will get exactly two black marbles in at most three tries?

We illustrate using a tree diagram.

The Tree diagram shows the probability of drawing a black marble on 2 out of 3 draws.

The probability that we will get two black marbles in the first two tries is listed adjacent to the lowest branch, and it = 3 10

The probability of getting first black, second white, and third black = 3 20

Similarly, the probability of getting first white, second black, and third black = 3 25

Therefore, the probability of getting exactly two black marbles in at most three tries = 3 10 + = 3 20 + = 3 25 = 57 100

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A circuit consists of three resistors: resistor R 1 size 12{R rSub { size 8{1} } } {} , resistor R 2 size 12{R rSub { size 8{2} } } {} , and resistor R 3 size 12{R rSub { size 8{3} } } {} , joined in a series. If one of the resistors fails, the circuit stops working. If the probability that resistors R 1 size 12{R rSub { size 8{1} } } {} , R 2 size 12{R rSub { size 8{2} } } {} , or R 3 size 12{R rSub { size 8{3} } } {} will fail is . 07 size 12{ "." "07"} {} , . 10 size 12{ "." "10"} {} , and . 08 size 12{ "." "08"} {} , respectively, what is the probability that at least one of the resistors will fail?

Clearly, the that at least one of the resistors fails = 1 none of the resistors fails size 12{"the that at least one of the resistors fails"=1 - "none of the resistors fails"} {} .

It is quite easy to find the probability of the event that none of the resistors fails. We don't even need to draw a tree because we can visualize the only branch of the tree that assures this outcome.

The probabilities that R 1 size 12{R rSub { size 8{1} } } {} , R 2 size 12{R rSub { size 8{2} } } {} , R 3 size 12{R rSub { size 8{3} } } {} will not fail are . 93 size 12{ "." "93"} {} , . 90 size 12{ "." "90"} {} , and . 92 size 12{ "." "92"} {} respectively. Therefore, the probability that none of the resistors fails = . 93 . 90 . 92 = . 77 size 12{"the probability that none of the resistors fails "= left ( "." "93" right ) left ( "." "90" right ) left ( "." "92" right )= "." "77"} {} .

Thus, the probability that at least one of them will fail = 1 . 77 = . 23 size 12{"the probability that at least one of them will fail"=1 - "." "77"= "." "23"} {} .

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Source:  OpenStax, Applied finite mathematics. OpenStax CNX. Jul 16, 2011 Download for free at http://cnx.org/content/col10613/1.5
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