6 The Excite Poll is an online poll at pollexcitecom You click on an answer to become part of the sample One poll question was Do you prefer watching firstrun movies at a movie theater or waiting until they are available on home video or payperview A total of 8896 people responde ID: 673221
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Slide1
Chapter 12
Sections 1-3Slide2
Bell Ringer
6. The Excite Poll is an online poll at poll.excite.com. You click on an answer to become part of the sample. One poll question was “Do you prefer watching first-run movies at a movie theater, or waiting until they are available on home video or pay-per-view?” A total of 8896 people responded with 1118 saying they preferred theaters. From this survey you can conclude that
a. Americans prefer watching movies at home.
b. a larger sample is necessary.
c. the poll uses voluntary response, so the results tell us
little
about the population of all adults.
d. movie theaters should lower their prices.Slide3
I CAN:Slide4
Daily Agenda
Bell Ringer
Review Bell Ringer
I CAN
Chapter
12
Sections 1-3Slide5Slide6Slide7Slide8Slide9Slide10
Random numbers are valuable. They are used to choose random samples, to shuffle the cards in online poker games, to encrypt our credit card numbers when we buy online, and as part of simulations of the flow of traffic and the spread of epidemics. Where does randomness come from, and how can we get random numbers? We defined randomness by how it behaves: unpredictably in the short run, but showing a regular pattern in the long run. Probability describes the long-run regular pattern. That many things are random in this sense is an observed fact about the world. Not all these things are “really” random. Here’s a quick tour of how to find random behavior and get random numbers.Slide11
The easiest way to get random numbers is from a computer program. Of course, a computer program just does what it is told to do. Run the program again, and you get exactly the same result. The random numbers in Table B, the outcomes of the Probability applet, and the random numbers that shuffle cards for online poker come from computer programs, so they aren’t “really” random. Clever computer programs produce outcomes that look random even though they really aren’t. These pseudorandom numbers are more than good enough for choosing samples and shuffling cards. But they may have hidden patterns that can distort scientific simulations.Slide12
12.2 Probability
Says…
Probability
is a measure of how likely an event is to occur. Match one of the probabilities that follow with each statement of likelihood given. (The probability is usually a more exact measure of likelihood than is the verbal statement.)
0 0.01 0.45 0.50 0.55 0.99 1
(a)This event is impossible. It can never occur.
(b)This event is certain. It will occur on every trial.
(c)This event is very likely, but it will not occur once in a while in a long sequence of trials.
(d)This event will occur slightly less often than not.Slide13
Gamblers have known for centuries that the fall of coins, cards, and dice displays clear patterns in the long run. The idea of probability rests on the observed fact that the average result of many thousands of chance outcomes can be known with near certainty. How can we give a mathematical description of long-run regularity?
To see how to proceed, think first about a very simple random phenomenon, tossing a coin once. When we toss a coin, we cannot know the outcome in advance. What do we know? We are willing to say that the outcome will be either heads or tails. We believe that each of these outcomes has probability 1/2. This description of coin tossing has two parts:
A list of possible outcomes
A probability for each outcome
Such a description is the basis for all probability models
.Slide14Slide15
In general, if all outcomes in a sample space are equally likely, we find the probability of any event bySlide16Slide17Slide18
12.5 Sample
Space
.
Choose
a student at random from a large statistics class. Describe a sample space S for each of the following. (In some cases, you may have some freedom in specifying S.)
(a)Does the student live on campus or off campus
?
(b)What is the student’s age in years
?
(c)What are the last four digits of the student’s cell phone number
?
(d)Record the student’s letter grade at the end of the course
.Slide19
12.6 Role-Playing
Games
. Computer games in which the players take the roles of characters are very popular. They go back to earlier tabletop games such as Dungeons & Dragons. These games use many different types of dice. A four-sided die has faces with one of the numbers 1, 2, 3, or 4 appearing at the bottom of each visible face.
(a)What is the sample space for rolling a four-sided die twice (numbers on first and second rolls)? Follow the example of Figure 12.2.
(b)What is the assignment of probabilities to outcomes in this sample space? Assume that the die is perfectly balanced, and follow the method of Example 12.4.Slide20
12.7 Role-Playing
Games
.
The intelligence of a character in a game is determined by rolling the four-sided die twice and adding 1 to the sum of the numbers. Start with your work in Exercise 12.6 to give a probability model (sample space and probabilities of outcomes) for the character’s intelligence. Follow the method of Example 12.5.