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Probability Part II

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Tree Diagram Used to show all of the possible outcomes of an experiment

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Example A couple plans on having 3 children. Assuming that the births are single births, make a tree diagram.

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Solution There are 8 birth orders. BBB BBG BGB BGG GBB GBG GGB GGG

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**Questions Find each probability: All 3 children are girls**

There is one girl There is at least one girl There is at most one girl

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**Answers Find each probability: All 3 children are girls 1/8**

There is one girl 3/8 There is at least one girl 7/8 There is at most one girl 4/8

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Independent events Two events, A and B, are independent if the occurrence of one event does not affect the probability of the occurrence of the other.

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**Examples Rolling a pair of dice Tossing 2 coins**

Drawing 2 cards from a deck if the first card is replaced before the second card is drawn

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Dependent events Two events, A and B, are dependent if the occurrence of one event does affect the probability of the occurrence of the other.

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Examples Drawing 2 cards from a deck of cards if the first card is not replaced before drawing the second card. Note: Without replacement is a clue that the events will be dependent.

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**Multiplication Rule Independent Events P(A and B) = P(A) * P(B)**

P(A and B) = P(A)*P(B|A) P(B|A) means probability of B assuming that A has happened. It is called a conditional probability.

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Example A die is rolled twice. What is the probability that the first roll is an even number and the second roll is a number greater than 4?

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**Solution These are independent events. P(even number) = 3/6**

P(number > 4) = 2/6 P(A and B) = 3/6 * 2/6 = 6/36 = 1/6

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Example Two cards are drawn from a deck of cards. What is the probability that both are Kings, if a. The first card is replaced before drawing the second card b. The first card is not replaced before drawing the second card

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**Solution There are 4 Kings in a deck of 52 cards. With replacement:**

= 0.006 Without replacement P = 4/52 * 3 / 52 = 0.005

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**Tables to find conditional probabilities**

A sample of 1000 people was obtained. There were 500 men and 500 women. Of the men, 63 were left handed. Of the women, 50 were left handed. Men Women Total Left handed 63 50 113 Right handed 437 450 887 500 1000

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Example What is the probability that the person is a male given the person is right handed?

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Example What is the probability that the person is a male given the person is right handed? Solution: There were 887 right handed people. Of these, 437 were men. P(M|RH) = 437/887 = 0.493

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Example What is the probability that person is right handed, given the person is male?

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Example What is the probability that person is right handed, given the person is male? Solution: There were 500 males. Of these, 437 were right handed. P(RH|M) = 437/500 = 0.874

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**Testing independence for a table**

Two events will be independent if P(B|A) = P(B)

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Example Are the events “male” and “right handed” independent or dependent?

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**Solution P(male) = 0.500 P(male|right handed) = 0.493**

These are not equal, so the 2 events are dependent. Note: You could also see if P(right handed) = P(right handed|male)

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Conditional Probability and the Multiplication Rule

Conditional Probability and the Multiplication Rule

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