1. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Chapter 14 From Randomness to Probability

2. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 14- 2 Dealing with Random Phenomena A random phenomenon is a situation in which we know what outcomes ___________ happen, but we don’t know which particular outcome ______ or ________ happen.

3. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 14- 3 Probability The probability of an event is its long-run ____________ ____________________. While we may not be able to predict a ____________ ___________________________, we can talk about what will happen ____________________________. For any random phenomenon, each attempt, or trial, generates an ___________________. Something happens on each trial, and we call whatever happens the __________________. These outcomes are __________________________, like the number we see on top when we roll a die.

4. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 14- 4 Probability (cont.) Sometimes we are interested in a combination of outcomes (e.g., a die is rolled and comes up even). A combination of outcomes is called ______________. When thinking about what happens with combinations of outcomes, things are simplified if the individual trials are ______________________. Roughly speaking, this means that the outcome of one trial doesn’t _________________ or ____________ the outcome of another. For example, coin flips are independent. Non-ex. ?

5. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 14- 5 The Law of Large Numbers The Law of Large Numbers (LLN) says that the long-run relative frequency of repeated independent events gets ___________________ to the true relative frequency as the number of trials increases. For example, consider flipping a fair coin many, many times. The overall percentage of heads should settle down to about _____% as the number of outcomes increases.

6. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 14- 6 The Law of Large Numbers (cont.) The common (mis)understanding of the LLN is that random phenomena are supposed to ________________ some for whatever happened in the past. This is just not true. For example, when flipping a fair coin, if heads comes up on each of the first 10 flips, what do you think the chance is that tails will come up on the next flip? Roulette Discussion

7. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 14- 7 Probability Thanks to the LLN, we know that ____________ ______________ settle down in the long run, so we can officially give the name ______________ to that value. Probabilities must be between ___ and ___, inclusive. A probability of 0 indicates ______________. A probability of 1 indicates ______________.

8. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 14- 8 Equally Likely Outcomes When probability was first studied, a group of French mathematicians looked at games of chance in which all the possible outcomes were ______________________. It’s equally likely to get any one of _____ outcomes from the roll of a fair die. It’s equally likely to get __________ or _________ from the toss of a fair coin. However, keep in mind that events are not always equally likely. A skilled basketball player has _____________ 50-50 chance of making a free throw.

9. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 14- 9 Personal Probability In everyday speech, when we express a degree of uncertainty without basing it on long-run relative frequencies, we are stating ___________ or ___________________________. Personal probabilities don’t display the kind of ___________________ that we will need probabilities to have, so we’ll stick with formally defined probabilities.

10. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 14- 10 Formal Probability 1.Two requirements for a probability: A probability is a number between ___ and ____. For any event A, __________________.

11. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 14- 11 Formal Probability (cont.) 2.“Something has to happen rule”: The probability of the set of all possible outcomes of a trial must be ____. P(S) = 1 (S represents the set of all possible outcomes.)

12. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 14- 12 Formal Probability (cont.) 3.Complement Rule:  The set of outcomes that are ____________ ________________ A is called the _____________________ of A, denoted ___.  The probability of an event occurring is 1 minus the probability that it doesn’t occur: _________________

13. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 14- 13 Formal Probability (cont.) 4.Addition Rule: Events that have no outcomes in common (and, thus, cannot occur together) are called __________ (or ______________________).

14. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 14- 14 Formal Probability (cont.) 4.Addition Rule: For two disjoint events A and B, the probability that one ___ the other occurs is the ______ of the probabilities of the two events. P(A or B) = ____________, provided that A and B are disjoint.

15. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 14- 15 Formal Probability (cont.) 5.Multiplication Rule: For two ________________ events A and B, the probability that both A and B occur is the ______________ of the probabilities of the two events. P(A and B) =________________, provided that A and B are independent.

16. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 14- 16 Formal Probability (cont.) 5.Multiplication Rule: Two independent events A and B are not _____________, provided the two events have probabilities greater than zero:

17. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 14- 17 Formal Probability (cont.) 5.Multiplication Rule: Many Statistics methods require an ____________________________, but assuming independence doesn’t make it true. Always Think about whether that assumption is __________________ before using the Multiplication Rule.

18. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 14- 18 Just Checking Opinion polling organizations contact their respondents by telephone. Random telephone numbers are generated, and interviewers try to contact those households. In the 1990’s this method could reach about 69% of U.S. households. According to the Pew Research Center for the People and the Press, by 2003 the contact rate had risen to 76%. Each household, of course, is independent of the others. a) What is the probability that the interviewer will successfully contact the next household on the list? b) What is the probability that an interviewer successfully contacts both of the next two households on her list? c) What is the probability that the interviewer’s first successful contact will be the third household on the list? d) What is the probability the interviewer will make at least one successful contact among the next 5 households on the lists?

19. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 14- 19 Assignment P.339 #2, 7, 10, 11, 13, 15, 24, 26, 27, 34

20. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Chapter 14 From Randomness to Probability (2)

21. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 14- 21 Formal Probability - Notation Notation alert: In this text we use the notation P(A or B) and P(A and B). In other situations, you might see the following: P(A ___ B) instead of P(A ___ B) P(A ___ B) instead of P(A ____ B)

22. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 14- 22 Putting the Rules to Work In most situations where we want to find a probability, we’ll use the rules in _____________. A good thing to remember is that it can be easier to work with the _________________ of the event we’re really interested in.

23. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 14- 23 What Can Go Wrong? Beware of probabilities that don’t ____________ __________. To be a legitimate probability distribution, the sum of the probabilities for _______________ __________________________ must total 1. Don’t add probabilities of events if they’re not _____________. Events must be disjoint to use the _________ ____________.

24. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 14- 24 What Can Go Wrong? (cont.) Don’t __________ probabilities of events if they’re not ______________. The multiplication of probabilities of events that are not __________________ is one of the most common errors people make in dealing with probabilities. Don’t confuse _________ and __________________—disjoint events can’t be independent.

25. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 14- 25 What have we learned? Probability is based on _____________________ ____________________. The Law of Large Numbers speaks only of _____ __________________________. Watch out for ___________________ the LLN.

26. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 14- 26 What have we learned? (cont.) There are some basic rules for ______________ probabilities of outcomes to find probabilities of more _______________________. We have the: Something Has to Happen Rule ______________________ Rule _______________ Rule for disjoint events _____________________ Rule for independent events

27. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 14- 27 Practice P. 340 #17, 19, 31

28. Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 14- 28 Assignment P.339 #6, 8, 12, 14, 16, 23, 25, 28, 33, 36