1. Chapter 4 Elementary Probability Theory

2. What is Probability?  Probability is a numerical measure between 0 and 1 that describes the likelihood that an event will occur. Probabilities closer to 1 indicate that the event is more likely to occur. Probabilities closer to 0 indicated that the event is less likely to occur.

3. Note:  P(A) = probability of event A; you read it as “P of A”.  P(A)=1, the event A is certain to occur  P(A)=0, the event A is certain to not occur  Binary number works like this…1 means it’s true, 0 means false.

4. See if you understand this statement:  “There are only 10 types of people in the world: those who understand binary, and those who don't”

5. Anyways…Probability Assignments

6. Examples  Intuition – NBA announcer claims that Kobe makes 84% of his free throws. Based on this, he will have a high chance of making his next free throw.  Relative frequency – Auto Fix claims that the probability of Toyota breaking down is.10 based on a sample of 500 Toyota of which 50 broke down.  Equally likely outcome - You figure that if you guess on a SAT test, the probability of getting it right is.20

7. Group Work  Create a situation for each of the probability assignments. (intuition, relative frequency, equally likely outcome)  Show me

8. Law of Large Numbers  In the long run, as the sample size increases, the relative frequencies of outcomes get closer to the theoretical (or actual) probability value  Example: The more numbers you ask, the more likelihood that P(getting a girl’s real number)=1

9. Law of Large Numbers examples:  The more numbers you ask, the more likelihood that P(getting a (hot) girl’s real number)=1  Then after collecting all the numbers, the more girls you ask out on a date, the more likelihood that P(getting a date)=1

10. Some other real life examples:  Casino (the more you play, the more you lose)  Insurance (the more people you insure, the less the likelihood the company have to pay for the insurance benefits)

11. Statistical Experiment  Statistical experiment or statistical observation can be thought of as any random activity that results in a definite outcome  An event is a collection of one or more outcomes of a statistical experiment or observation  Simple event is one particular outcome of a statistical experiment  The set of all simple events constitutes the sample space of an experiment

12. Example: Blue eyes vs Brown eyes (relating to biology)  Brown eyes’ genotype is Bb or BB  Blue eyes’ genotype is bb  If your Dad has Brown eyes (and his dad has blue eyes) and your Mom has blue eyes, what’s the probability that you have blue eyes?

13. Answer (using sample space) Bb bBbbb bBbbb Dad Mom

14. Group Work (use sample space):  You are running out of time in a true/false quiz. You only have 4 questions left! How should you guess?  P(all false)= P(3 false)=  P(all true)= P(2 false)=  P(1 true)= P(1 false)=  P(2 true)=  P(3 true)=

15. Answer  Your sample space should have 16 different combinations  P(all false)= 1/16 P(3 false)= 4/16  P(all true)= 1/16 P(2 false)= 6/16  P(1 true)= 4/16 P(1 false)= 4/16  P(2 true)= 6/16  P(3 true)= 4/16  You will probably choose 2 true and 2 false TTTTFTTTTFTTTTFT TTTFFFTTFTFTFTTF TFFTTFTFTTFFFFFT TFFFFTFFFFTFFFFF

16. Note:

17. Example:  P(getting A in Mr. Liu’s class)+P(not getting A in Mr. Liu’s class) =1  P(getting A in Mr. Liu’s class)=.15  What’s the P(not getting A in Mr. Liu’s class)?

18. Answer  P(not getting A in Mr. Liu’s class)=.85

19. Group Work  P(having a date on a Friday)=1/7  What’s the P(not having a date on a Friday)?

20. Answer  6/7

21. Homework Practice:  Pg 130 #1-6 (all), 7-13 (odd)

22. Compound Events

23. Consider these two situation  P(5 on 1 st die and 5 on 2 nd die)  P(ace on 1 st card and ace on 2 nd card)  What is the difference between these two situation?

24. The answer  In the first situation, the first result does not effect the outcome of the 2 nd result.  In the second situation, the first result does effect the outcome of the 2 nd result.

25. Independent  Two events are independent if the occurrence or nonoccurrence of one does not change the probability that the other will occur  What does it mean if two events are dependent?

26. Multiplication rule for independent events

27. What if the events are dependent?  Then we must take into account the changes in the probability of one event caused by the occurrence of the other event.

28. Sample Space A B A and B

29. General multiplication rule for any events

31. Conditional Probability Example:  Your friend has 2 children. You learned that she has a boy named Rick. What is the probability that Rick’s sibling is a boy?  Take a guess

32. Answer

33. Group Work  A machine produce parts that’s either good (90%), slightly defective (2%) or obliviously broken (8%). The parts gets through an automatic inspection machine that is able to find the oblivious broken parts and throw them away. What is the probability of the quality part that make it through and get shipped?

34. Answer

35. Relax!  Conditional Probability can be very intriguing and complicated. We won’t go into any more in depth…..or maybe….

36. Note: Very important to understand about probability is that are the events dependent or independent.

37. Group Work  Suppose you are going to throw 2 fair dice. What is the probability of getting a 3 on each die?  A) Is this situation independent or dependent?  B) Create all the sample space (all the potential outcomes)  C) What is the probability?

38. Answer  A) Independent because one event does not affect the second event  B) You should have 36 total outcomes  C) 1/36

39. Group Work  I took a die away. Now you only have ONE die! Again you toss the die twice. What is the probability of getting a 1 on the first and 4 on the second try?

40. Answer  It is still an independent event!  1/36

41. Note:  The last two examples are considered multiplication rule, independent events.

42. Group Work  Mr. Liu has a 80% probability of teaching statistics next year. Mr. Riley has a 15% probability of teaching statistics next year. What is the probability that both Mr. Liu and Mr. Riley teach statistics next year?

43. Answer .8*.15=.12 or 12% probability

44. Now comes the dependent events  Suppose you have 100 Iphones. The defective rate of iphone is 10%. What is the probability that you choose two iphones and both are defective?

45. Answer

46. Group work  What is the probability of getting tail and getting a 3 on a die and getting an ace in a deck of cards?

47. Answer

48. Addition Rules  You use addition when you want to consider the possibility of one event OR another occurring

49. Example:

50. Group Work: And or Or?  1) Satisfying the humanities requirement by taking a course in the history of Japan or by taking a course in classical literature  2) Buying new tires and aligning the tires  3) Getting an A in math but also in biology  4) Having at least one of these pets: cat, dog, bird, rabbit

51. Answer  1) or  2) and  3) and  4) or

52. Note:  Two events are mutually exclusive or disjoint if they cannot occur together. In particular, events A and B are mutually exclusive if P(A and B)=0

53. Addition rule for mutually exclusive events A and B  P(A or B)=P(A)+P(B)  General Rule for any events A and B  P(A or B)=P(A)+P(B)-P(A and B)  Remember in mutually exclusive events P(A and B)=0

54. Group Example: Employee type Democrat (D) Republican (R) Independent (I) Row Total Executive (E) 534948 Production Worker (PW) 6321892 Column Total685517140 grand total

55. Answer

56. Homework Practice:  Pg 146 #1,2,5,7,9,10,14,19

57. Conditional Probability extension  Bayes’s theorem: It uses conditional probabilities to adjust calculations so that we can accommodate new relevant information.  The special case where event B is partitioned into only two mutually exclusive events.

58. Formula

59. Example (Real Life Extension): How accurate is “one” pregnancy test?  Supposedly pregnancy test strip claims it is 99% accurate.  false-positive and false-negative NOT PregnantPregnant!!!! Pregnancy Test Negative True NegativeFalse Negative Pregnancy Test Positive False Positive True Positive!!

60. Procedure

61. Trees and Counting Techniques

62. Tree diagram:  A tree diagram shows all the possible outcomes of an event.  All possible outcomes of an event are shown by a tree diagram.

63. Example using tree diagrams:  If a coin and a dice are tossed simultaneously, what is the probability of getting tail and even number?

64. Answer  1/4

65. Group Work using tree diagram:  You are on a sports team. What is the probability that out of three games, you win two of them?

66. Tree Diagram with Probability:  You have 7 balls, 4 are blue and 3 are green. What is the probability that when you pick the balls, you get green on 1 st and blue one 2 nd ?

67. Shown in class

68. Group Work:  You make free throws 85% of the time. What is the probability of making at least one out of the three?

69.  P(make 1 out of 3)=99.66% of the time

70. Factorials  ! Means factorial  0!=1  1!=1  n!=(n)(n-1)(n-2)(n-3)….

71. What is 6! ?  6!=6*5*4*3*2*1=720

72. Combination vs Permutation

73. Combination:  Order does not matter! It is not important  If you have 3,1,2, it is the same as 1,3,2 because they all have 1,2,3  Different Arrangement of things  Combination is choosing

74. Permutation:  Order does matter! It is important  Note: Permutation is position

75. Combination vs Permutation continue:  Both of them break down into two different category:  Combination with repetition (ex: ice cream scoops)  Combination without repetition (ex: lottery)  Permutation with repetition (ex: lock in locker room)  Permutation without repetition (ex: marathon race)

76. Reading activity:  http://www.mathsisfun.com/combinatorics/combinations -permutations.html http://www.mathsisfun.com/combinatorics/combinations -permutations.html  Read the different examples

77. Whew that was a lot of reading…now do some examples.  You have 8 people, what are the number of possible ordered seating arrangement for 5 chairs

78. Answer

79. Group Work: Gamestop has 25 new games this month and you decided to buy 5 of them. How many different arrange of game you can have?

80. Answer

81. Group Work: MEGA Million  What is the chance of winning the jackpot for MEGA Million?  You have 5 slots + 1 slot for MEGA number  The first 5 slots are numbers between 1-75, mega number is number between 1-15

82. Answer

83. Group Work: Powerball lottery  What is the chance of winning the Jackpot for Powerball?  You have 5 slots+1 slot for Power number  The first 5 slots are numbers between 1-56, powerball slot is number between 1-35

84. Answer  1 in 175,223,510

85. Interesting fact  Even though it’s harder to win the Jackpot, for overall winning chance, you have more chance for MEGA million than Powerball

86. Homework Practice  Pg 160 #1-27 every other odd