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Introductory Statistics Lesson 3.2 A Objective: SSBAT find conditional probability. Standards: M11.E.3.1.1.

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Presentation on theme: "Introductory Statistics Lesson 3.2 A Objective: SSBAT find conditional probability. Standards: M11.E.3.1.1."— Presentation transcript:

1 Introductory Statistics Lesson 3.2 A Objective: SSBAT find conditional probability. Standards: M11.E.3.1.1

2 Conditional Probability  The probability of an event occurring, given that another event has already occurred.  Notation: P(B│A) means Probability of event B occurring given event A has occurred P(A│B) means Probability of event A occurring given event B has occurred

3 Examples. 1.Two cards are selected in sequence from a deck of cards. Find the probability that he second card is a queen, given that the first card is a king. The king is not replaced.  Since the first card was a King and it was not replaced, there are now just 51 cards remaining, with 4 queens. P(Q│K) =

4 2.Two cards are chosen in sequence from a deck of cards. Find the probability that the second card is a heart, given the first card was the 10 of hearts. The first card is not replaced.  After the first card is chosen, there are just 51 cards remaining. The first card was also a heart, so now there are just 12 hearts. P(Heart│10 of Hearts) =

5 3.The table shows the results of a study in which researchers examined a child’s IQ and the presence of a specific gene in the child. Find the probability that a child has a high IQ, given that the child has the gene. Gene Present Gene not present Total High IQ 331952 Normal IQ 391150 Total 7230102

6 4.Use the same table to find the Probability that a child does not have the gene, given that the child has a normal IQ. Gene Present Gene not present Total High IQ 331952 Normal IQ 391150 Total 7230102  We are given the child has a Normal IQ, so therefore we will just use this data (row).  There are a total of 50 children who have a normal IQ. P(No Gene│Normal IQ) =

7 Independent Events  Two events are Independent if the occurrence of one of the events does NOT affect the probability of the other event.  Example - Rolling a Die and Tossing a Coin What you roll on the die does not affect what you toss on the coin.  If events are not independent they are Dependent

8 Examples: Determine if the events are Independent or Dependent 1.Selecting a King from a deck of cards, not replacing it, and then selecting a Queen from the deck.  Dependent (not replacing the king changes the probability of selecting a queen) 2.Tossing a coin and getting a head, and then rolling a die and getting a 6.  Independent (what you get on the coin does not affect what you get on the die)

9 3.Driving 80 miles per hour and then getting a speeding ticket.  Dependent 4.Smoking a pack of cigarettes per day and developing emphysema (a lung disease)  Dependent 5. Exercising frequently and having a 4.0 grade point average  Independent

10 Complete worksheet 3.2 A


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