Objective 1: Simple Probability

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Objective : Simple Probability To find the probability of event E, P(E) number of ways event E can occur total number of outcomes in sample space Example : In a pet store, there are 5 puppies, 22 kittens, and 8 rabbits. What is the probability of randomly selecting a rabbit? P(rabbit) number of rabbits total number of pets in store 8 55 0.3273 Example 2: The following data represent the number of classes a student is taking and their gender. What is the probability that a randomly selected student is taking class? P( class) number of students taking class total number of students 8 0.93 Example 3: What is the probability of drawing a heart from a standard -card deck? Number of hearts 3 P(Heart) Total number of cards

Objective 2: Addition Rule for Disjoint Events Definition: Two events, E and F, are disjoint (or mutually exclusive) if they have no outcomes in common. Addition Rule for Disjoint (Mutually Exclusive) Events If two events E and F are disjoint, then the probability of event E OR the probability of event F occurring is P(E OR F) P(E) + P(F) Example : What is the probability of drawing a king or a queen from a standard deck of playing cards? P(King OR Queen) P(King) + P(Queen) 8 2 3 0.538 + Example 5: The following data represent the number of classes a student is taking and their gender. What is the probability that a randomly selected student is taking 2 classes or 3 classes? class 2 classes 3 classes + classes TOTAL Female 3 35 56 28 32 Male 35 29 38 3 5 TOTAL 8 6 9 P(2 classes OR 3 classes) P(2 classes) + P(3 classes) 6 58 0.6397 + 9 2

Objective 3: General Addition Rule If two events are not disjoint, which means they do have outcomes in common, then you should use the General Addition Rule. General Addition Rule For ANY two events E and F, then the probability of event E OR the probability of event F occurring is P(E OR F) P(E) + P(F) P(E AND F) Example 6: What is the probability of drawing a diamond or a king from a standard deck of playing cards? P(Diamond OR King) P(Diamond) + P(King) P(Diamond AND King) 3 + 6 3 0.3077 Example 7: The following data represent the number of classes a student is taking and their gender. What is the probability that a randomly selected student is a female or taking 3 classes? class 2 classes 3 classes + classes TOTAL Female 3 35 56 28 32 Male 35 29 38 3 5 TOTAL 8 6 9 P(Female OR 3 classes) P(Female) + P(3 classes) P(Female AND 3 classes) 32 + 9 56 70 0.6883 3

Objective : Complement Rule Definition: Let E be any event. Then, the complement of E, denoted as E c, is all the outcomes in the sample space that are NOT outcomes in the event E. Complement Rule If E represents any event and E c represents the complement of E, then P(E c ) P(E) and P(E) P(E c ) Example 8: What is the probability of not drawing a spade card from a standard deck of playing cards? P(Not Spade) P(Spade) 3 39 Example 9: According to the Pew Research Group, 8% of teens use social media networks. What is the probability that a randomly selected teen does not use social media networks? 3 P(Not Social Media User) P(Social Media User) 0.8 0.9 Objective 5: Multiplication Rule for Independent Events Definition: Two events E and F are independent if the occurrence of event E does not affect the probability of event F. Two events are dependent if the occurrence of event E does affect the probability of event F. Multiplication Rule for Independent Events If E and F are independent events, then the probability of event E AND event F occurring would be P(E AND F) P(E) P(F) Example 0: A die is rolled and a coin is flipped. What is the probability that the result of the die is a 5 and the coin comes up heads? P(5 AND Heads) P(5) P(Heads) 6 2 2

Example : According to the Pew Research group, 95% of teens use the internet. Suppose four teens are randomly selected. What is the probability that all four use the internet? P(all use internet) P(st uses internet) P(2nd uses internet) P(3rd uses internet) P(th uses internet) 0.95 0.95 0.95 0.95 (0.95) 0.85 Objective 6: Conditional Probability Definition: The conditional probability, denoted as P(E F), is the probability that event E occurs GIVEN that event F has already occurred. Conditional Probability If E and F are any events, then the conditional probability, P(E F), can be found by P(E F) P(E AND F) P(F) or P(E F) number of outcomes in E AND F number of outcomes in F Example 2: According to the U.S. National Center for Health Statistics, in 997, 0.2% of deaths in the U.S. were of 25 3 year olds whose cause of death was cancer. In addition,.97% of all people who died were 25 3 years old. What is the probability that a randomly selected death is the result of cancer, if the individual is known to have been 25 3 years old? P(Death due to cancer 25 3 years old) P(Cancer AND 25 3 yrs old) P(25 3 yrs old) 0.002 0.097 0.05 5

Example 3: The following data represent the number of classes a student is taking and their gender. What is the probability that a randomly selected student is taking 3 classes, given that the student is male? class 2 classes 3 classes + classes TOTAL Female 3 35 56 28 32 Male 35 29 38 3 5 TOTAL 8 6 9 P(3 classes male) number of people who are taking 3 classes AND male number of people who are male 38 5 0.330 Objective 7: General Multiplication Rule (Dependent Events) If we have two events E and F and event F does affect event E (E and F are dependent events), then the probability that E and F both occur is P(E AND F) P(E) P(F E) Example : Suppose two cards are randomly selected from a standard deck of playing cards. What is the probability that the first card is a club and the second card is also a club if the draw is done without replacement? P(st club AND 2nd club) P(st club) P(2nd club st club) 3 2 5 56 26 7 0.0588 6