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Probability Rules!!!!!!

Probability Rules!!!!!!. Probability. Definition : a measure of how likely it is that some event will occur. It can be expressed as a ratio of the number of favorable outcomes (i.e. a head coming up) over the total number of cases. . Spinning Pennies!.

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Probability Rules!!!!!!

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  1. Probability Rules!!!!!!

  2. Probability • Definition: a measure of how likely it is that some event will occur. It can be expressed as a ratio of the number of favorable outcomes (i.e. a head coming up) over the total number of cases.

  3. Spinning Pennies! • Place the penny on its edge Lincoln side facing you. • Lightly hold the penny with one hand and flick it with the other. • Let it spin until falling. • Record the outcome. • Run 30 trials. • We’ll collect class data.

  4. Suppose you’d only spun the penny twice….. Would our results look different? • Why do you know the proportion of heads should be 50% of the number of trials?

  5. You will win a prize if you toss a coin a given number of times and get between 40% and 60% heads. Would you rather toss the coin 10 times or 100 times? • You will win a prize if you toss a coin a given number of times and get exactly 50% heads. Would you rather toss the coin 10 times or 100 times?

  6. Trials, Outcomes & Events • Trial • Definition: A single attempt of a random phenomenon. • Outcome • Definition: the outcome of a trial is the value measure, observed, or reported for an individual instance of that trial. • Event • Definition: a collection of outcomes.

  7. Experimental Probability • Definition: the ratio of the number of successes over the total number of trials. • For example…the number of heads you got in your experiment divided by the total number of coin flips. • It is experimental because it comes from the actual results of your experiment.

  8. Experimental Probability • Experimental probability can be expressed as: where f is the frequency (# of successes) and n is the number of trials. • Who can provide an example of experimental probability?

  9. Randomness • A phenomenon is random if we know what outcomes could happen, but not which particular values did or will happen. • Probability is the art of summarizing this randomness using theoretical probability.

  10. Sample Space • Definition: the sample space is the collection of all possible outcomes from a given event. • Example: If the event is tossing a coin once, then the sample space is S = { H, T } • Example: If the event is rolling a die once, then the sample space is S = { 1, 2, 3, 4, 5, 6 }

  11. Theoretical Probability • Definition: The actual probability of an event occurring. • Only works when each outcome in a sample space has an constant defined chance of occurring. • Can anyone think of an example of theoretical probability?

  12. Probability Rules • A probability is a number between 0 and 1. • Something Has To Happen Rule. The probability of SOMETHING happening is always 1. • Complement Rule. The probability of an event occurring is 1 minus the probability that it doesn’t occur.

  13. Disjoint Events • Two events are disjointif they share no outcomes in common. • If A and B are disjoint, then knowing that A occurs tells us that B cannot occur. • Disjoint events are also called “mutually exclusive”. • The blood type, think Venn diagram where circles can’t overlap

  14. Independent Events • Definition: if the outcome of one event does not affect the probability of a second event the two events are considered independent. • Ex: We are going to perform the following experiment. First flip a coin, second roll a die. Regardless of what outcome I get for the coin flip, I will still have a 1/6 chance of rolling any one particular side of the dice. • not disjoint, b/c can happen at same time

  15. Probability Rules • Addition Rule. For two disjoint events A and B, the probability that one or the other occurs is the sum of the probabilities of the two events.P(A or B) = P(A) + P(B) ,provided that A and B are disjoint. • Multiplication Rule. For two independent events A and B, the probability that both A and B occur is the product of the two events.P(A and B) = P(A)*P(B)

  16. What can go Wrong? • Don’t confuse “disjoint” with “independent”. • Disjoint events cannot happen at the same time. When one happens, you know that other did not. • Independent events must be able to happen at the same time. When one happens, you know it has no effect on the other.

  17. Probability practice • Here are the probabilities that the person you choose will have blood type O, A, or B. O = .49, A = .27, B = .20 • What is the probability of someone with the remaining blood type AB? • What is the probability that the person chosen has either type A or type B blood?

  18. A generic M&M bag had the following colors and probabilities of getting that color: brown=.3; red=.2, yellow=.2; green=.1; Orange=.1; What does P(blue)=? • What is the probability that the candy drawn is not red, yellow, or orange?

  19. Create the sample space for a couple having 3 children, assume 50/50 boy/girl. • Find the probability that when a couple has 3 children, they will have exactly 2 boys. Assume that boys and girls are equally likely and that gender for any child is not influenced by the gender of any other child!

  20. In a large Intro to Stats class, the professor reports that 55% of the students have never taken Calculus, 32% have taken only one semester, and the rest have taken two or more. The prof randomly assigns students to groups of three to work on a project. What is the probability that the first group mate you meet has studied… • Two or more semesters of Calc? • Some Calc? • No more than one semester of Calc?

  21. Another project: You are assigned to be part of a group of three students from the Intro to Stats class, from the last problem. What is the probability that of your other two group mates, • Neither studied Calc? • Both have studied at least one semester of Calc? • At least one has some Calc?

  22. Final Project: You used the Multiplication Rule to calculate the probabilities about the Calculus background of your stats group mates from the last problem. • What must be true about the groups in order to make that approach valid? • Do you think this assumption is reasonable? Why?

  23. Opinion polling interviewers are able to reach about 65% of US households, of those contacted those that participate has fallen from 48% in 1997 to only 36% in 2003. Each house is independent of the other… • What is the prob. (2003) of the next house on the list will be contacted, but refuse to cooperate? • What is the prob. (2003) of failing to contact a house or of contacting the house but not getting them to agree to the interview?

  24. In 1997 the contact rate was 48% and in 2003 it was 36%. • However the cooperation rate was just used: 58% in 1997 and 38% in 2003. • What is the prob. (2003) of obtaining an interview with the next call? (contacting house and agree) • Was it more likely to obtain an interview from a randomly selected house in 1997 or 2003?

  25. The Red Cross says that about 35% of the US population has Type O blood, 30% Type A, 18% Type B, and the rest AB • Someone volunteers to give blood. What is the probability that this donor • Has type AB blood? • Has type A or Type B? • Is not type O

  26. The Red Cross says that about 35% of the US population has Type O blood, 30% Type A, 18% Type B, and the rest AB • Among 4 potential donors, what is the prob that.. • All are type O? • No one is type AB? • They are not all Type A? • At least one person is Type B?

  27. A slot machine has three wheels that spin independently. Each has 10 equally likely symbols: 3 bars, 4 lemons, 2 cherries, and a bell. If you play what is the probability • You get three lemons? • You get a bell or a cherry on each? • You get no fruit symbols? • You get 3 bells (jackpot)? • You get no bells? • You get at least one bar (lose automatically)?

  28. For a sales promotion, the manufacturers of Coke places winning symbols under the caps of 8% of all Coke bottles. You buy a six-pack. What is the probability that you win at least once?

  29. You shuffle a deck of cards, and then start turning them over one at a time. The first one is read. So is the second. And the third. In fact, you are surprised to get 10 red cards in a row! • You start thinking, “The next cards is due to be black!” • Are you correct in thinking that there’s a higher probability that the next cards will be black than red? Let’s discuss

  30. Dependent Events • Definition: when the outcome of one event does affect the possible outcomes of another event, the events are called dependent events. • Ex: You have 5 cards in a jar. Two of them have a picture of a Giraffe on them. The other three have a picture of a Blue Whale on them. What is the probability that the first two cards I select are both cards with Giraffes on them one after the other? • LOOK AT THE SAMPLE SPACE! Make a table or chart!

  31. Sample Spaces… • For each of the following, list the sample space and tell whether you think the outcomes are equally likely. • Toss 2 coins; record the order of heads and tails • A family has 3 children; Record the number of boys • A family has 3 children; record the genders in order of birth • Roll two dice; record the greater number

  32. Probability Rules • General Addition Rule. For any two events, then the probability of A or B is…P(A U B) = P(A) + P(B) – P(A ∩ B) • Conditional Probability. The probability of B given that A happens is…P(B|A) =

  33. General Addition Rule • Real estate ads suggest that 64% of homes for sale have garages, 21% have swimming pools, and 17% have both features. What is the probability that a home for sale has • A pool or a garage? • Neither a pool nor a garage? • A pool but no garage?

  34. General addition Rule • If we searched through the book to check out the number of pages with a data display on it we’d find: 48% some kind of display, 27% had an equation, 7% had both data display and equation • Display these results in a Venn diagram • Find prob: random page had neither a display or equation. • Find prob: random page had a data display but no equation.

  35. Police report that 78% of drivers stopped on suspicion of drunk driving are given a breath test, 36% a blood test, and 22% both tests. What is the probability that a randomly selected DWI suspect is given • Create a Venn diagram to display these results. • A test? • A blood test or breath test, but not both? • Neither test?

  36. In How Americans Exercise, a study presented the following information on what people do to stay fit: 53% jog, 44% swim, 46% cycle, 18% jog and swim, 15%swim and cycle, 17% jog and cycle, and 7% jog, swim, and cycle. • Find prob that a person jogs or swims. • Cycles or jogs • Does neither swimming nor cycling. • Does only one of the three exercises. • Are there any people in the study who don’t exercise?

  37. Probability Rules • General Addition Rule. For any two events, then the probability of A or B is…P(A U B) = P(A) + P(B) – P(A ∩ B) • Conditional Probability. The probability of B given that A happens is…P(B|A) =

  38. Conditional Probability • P(sports) • P(Sports|Girl) • P(Girl|Popular) • P(Sports|Boy) • P(Boy|Grades)

  39. Conditional Probability • P(Second Class|Dead) • P(Dead|Second Class) • P(Crew|Alive) • P(Alive|First)

  40. Survey assessing who’s been to what Boston landmark • What proportion of students who have been to the Aquarium are female? • What proportion of students who have been to Fenway are female? • What proportion of students who have been to the Museum of Art are female? • Do you think one landmark has a bigger draw than others for the female population? Or can we make that conclusion? • What is the probability that a male has gone to the Aquarium?

  41. People who have seen James Cameron’s movies; random study • What is the probability that someone has seen Point Break? • What is the probability a freshman has seen Point Break? • What’s the probability of those people who have seen Point Break we select a freshman? • What would be the probability that a senior has seen Point Break? • Do you think number of movies watched depends on age? • Are there any lurking variables?

  42. Survey asking about Pizza Preference • Find the probability that cheese was selected given the customer was a female. • Find the probability that cheese was selected given the customer was a male. • What is the probability that cheese pizza was selected in this study. • What question would give us the highest probability? • How much higher is the proportion of male’s that order meat than that of female’s?

  43. Conditional Probability • In Brighton the probability that a married man drives is .90. If the probability that a married man and his wife both drive is .85, what is the probability that his wife drives given that he drives?

  44. Conditional Probability • Jackie often speeds while driving to school in order to arrive on time. The probability that she will speed to school is .75. If the probability that she speeds and gets stopped by a police officer is .25, find the probability that she is stopped, given that she is speeding.

  45. Conditional Probability • John likes to study. The probability that he studies and passes his math test is .80. If the probability that he studies is .83, what is the probability that he passes the math test, given that he has studied?

  46. Probability Rules • General Multiplication Rule. For any two events A and B (probably dependent), the probability of A and B is P(A∩B) = P(A)*P(B|A)

  47. Independence Again • Events A and B are independent if and only if…P(B|A) = P(B)

  48. What can go Wrong? • Don’t use a simple probability rule where a general rule is appropriate. • Don’t assume independence without reason to believe it. Don’t assume outcomes are disjoint without checking. • Remember…the general rules always apply even when outcomes are in fact independent or disjoint.

  49. Multiplication Rule • In the land of OZ the probability that a man over 40 is overweight is .42. The probability that his blood pressure is high given that he is overweight is .67. If a man over 40 years of age is selected at random, what is the probability that he is overweight and that he has high blood pressure?

  50. Multiplication Rule • Due to the rising cost of auto insurance, the probability that a randomly selected driver in Boston drives uninsured is 0.13. Moreover, the probability that the car’s driver is under 30 years old, given that the car is uninsured, is 0.39. If a driver is randomly selected, find the probability that the driver is under 30 and the car is uninsured.

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