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5-Minute Check on Section 6-3b

This lesson covers the concepts of probability and simulation, including performing simulations, using probability rules, and solving probability problems.

jorgeparker
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5-Minute Check on Section 6-3b

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  1. 5-Minute Check on Section 6-3b Given that P(A) = .25 , P(B) = .7, and P(B|A) = .6 find: P(A and B) P(A or B) P(A|B) Are A and B independent? Explain Given that the probability of a defective calculator is 0.07, if an inspector examines 2 calculators out of 20 in a box, what is the probability that at least one is defective? = P(B|A)•P(A) = 0.60.7 = 0.42 = P(A) + P(B) – P(A and B) = 0.25 + 0.7 - 0.42 = 0.53 P(A and B) 0.42 = ----------------- = -------- = 0.6 P(B) 0.7 No! P(A|B), 0.6 ≠ 0.25, P(A) P(at least 1) = 1 – P(none) = 1 – (0.93)(0.93) = 0.1351 Click the mouse button or press the Space Bar to display the answers.

  2. Lesson 6 - R Probability and Simulation:The Study of Randomness

  3. Objectives • Perform a simulation of a probability problem using a table of random numbers or technology • Use the basic rules of probability to solve probability problems • Write out the sample space for a random phenomenon, and use it to answer probability questions • Describe what is meant by the intersection and union of two events • Discuss the concept of independence • Use general addition and multiplication rules to solve probability problems • Solve problems involving conditional probability, using Bayes’s rule when appropriate

  4. Vocabulary • none new

  5. AP Outline Fit: III. Anticipating Patterns: Exploring random phenomena using probability and simulation (20%–30%) A. Probability 1. Interpreting probability, including long-run relative frequency interpretation 3. Addition rule, multiplication rule, conditional probability, and independence 5. Simulation of random behavior

  6. What we Learned • Simulation • Recognize that many random phenomena can be investigated by means of a carefully designed simulation. • Use the following steps to construct and run a simulation: • State the problem or describe the random phenomenon. • State the assumptions. • Assign digits to represent outcomes. • Simulate many repetitions. • Calculate relative frequencies and state your conclusions. • Use a random number table, the TI-83/84/89, or a computer utility such as Minitab, DataDesk, or a spreadsheet to conduct simulations.

  7. What we Learned • Probability Rules • Describe the sample space of a random phenomenon. For a finite number of outcomes, use the multiplication principle to determine the number of outcomes, and use counting techniques, Venn diagrams, and tree diagrams to determine simple probabilities. For the continuous case, use geometric areas to find probabilities (areas under simple density curves) of events (intervals on the horizontal axis). • Know the probability rules and be able to apply them to determine probabilities of defined events. In particular, determine if a given assignment of probabilities is valid.

  8. What we Learned • Probability Rules (continued) • Determine if two events are disjoint, complementary, or independent. Find unions and intersections of two or more events. • Use Venn diagrams to picture relationships among several events. • Use the general addition rule to find probabilities that involve intersecting events. • Understand the idea of independence. Judge when it is reasonable to assume independence as part of a probability model. • Use the multiplication rule for independent events to find the probability that all of several independent events occur.

  9. What we Learned • Probability Rules (continued) • Use the multiplication rule for independent events in combination with other probability rules to find the probabilities of complex events. • Understand the idea of conditional probability. Find conditional probabilities for individuals chosen at random from a table of counts of possible outcomes. • Use the general multiplication rule to find the joint probability P(A  B) from P(A) and the conditional probability P(B | A). • Construct tree diagrams to organize the use of the multiplication and addition rules to solve problems with several stages.

  10. Simulation • Imitation of chance behavior based on a model that accurately reflects phenomenon under consideration • Can use our calculator in many ways • ProbSim application • Random number generation • Can use a random number table (table b in book) • State the problem or describe the random phenomenon • State the assumptions • Assign digits to represent outcomes • Simulate many repetitions (trials) • State your conclusions

  11. Probability Rules • 0 ≤ P(any event) ≤ 1 • ∑ P(all events) = 1 (∑ is summation) • P(certainty) = 1 and P(impossibility) = 0 • Complement Rule: P(not occurring) = 1 – P(occurring) • Disjoint Events Rule: If two events have no outcomes in common (disjoint), then P(A or B) = P(A) + P(B) • Multiplication Rule: If A and B are independent (knowing if one event occurs does not change the probability of the other event), then P(A and B) = P(A)  P(B) • At least Probabilities: P(at least one) = 1 – P(complement of “at least one”) = 1 – P(none)

  12. General Multiplication Rule General Multiplication Rule: Probability that two events A and B both occur (regardless of independence) is P(A and B) = P(A  B) = P(A) ∙ P(B | A) where P(B | A) is a conditional probability read as the probability of B given that A has occurred Conditional Probabilities: If A and B are any two events, then P(A and B) N(A and B) P(B | A) = ----------------- = ---------------- P(A) N(A) where N is the number of outcomes

  13. Independence in Terms of Conditional Probability Two events A and B are independent if P(B | A) = P(B) Example: P(A = Rolling a six on a single die) = 1/6 P(B = Rolling a six on a second roll) = 1/6 no matter what was rolled on the first roll!! So probability of rolling a 6 on the second roll, given you rolled a six on the first is still 1/6P(B | A) = P(B) so A and B are independent

  14. Tree Diagram 0.8 Right-handed 0.44 = 0.550.8 • Tree diagrams can be used to determine right-end (conditional) probabilities by multiplying the probabilities as you get to the right end • Good analysis tool for AP problems Male 0.55 0.2 Left-handed 0.11 = 0.550.2 Sex Right-handed 0.84 0.378 = 0.450.84 0.45 Female Left-handed 0.16 0.072 = 0.450.16 1.0

  15. Contingency Tables Contingency tables are easy ways to show conditional probabilities. Givens eliminate other rows and columns from the calculations as seen in the examples below: • What is the probability of left-handed given that it is a male? • What is the probability of female given that they were right-handed? • What is the probability of being left-handed? P(LH | M) = 12/60 = 0.20 P(F| RH) = 42/90 = 0.467 P(LH) = 20/110 = 0.182

  16. Summary and Homework • Summary • Simulation with random numbers or calculator • Must know rules of probability • Conditional probability • From contigency tables • From formulas • P(At least one) = 1 – P(None) • Tree diagrams: useful tool for probabilities • Homework • pg 459 – 60; 6-98, 99, 101-106

  17. Problem 1a At a recent movie, 1000 patrons (560 females and 440 males) were asked whether or not they liked the film. In was determined that 355 females liked the film and 250 males said they enjoyed it also. If a person is randomly selected from the moviegoers what is the probability that the moviegoers was: a) male? b) a female and liked the film c) a male or someone who disliked the film? d) a male and disliked the film? e) a male given they liked the film? f) someone who liked the film given they were a female? g) Are sex and film preference independent? P(m) = 440/1000 = 0.44 P(F & L) = 0.56 * 355/560 = 0.44 P(m or DL) = 0.44 P(m & DL) = 0.44 P(m|L) = 250/605 = 0. P(L|F) = 355/560 = 0. P(M|L) = P(M)

  18. Problem 1b If P(A) = .3 and P(B) = .45 and events A and B are mutually exclusive find P(A or B). Mutually Exclusive  P(A and B) = 0!! P(A or B) = P(A) + P(B) – P(A and B) P(A or B) = 0.3 + 0.45 = 0.75

  19. Problem 1c When spot-checked for safety, automobiles are found to defective tires 15% of the time, defective lights 25% of the time, and both defective tires and lights 8% of the time. Find the probability that a randomly chosen car has defective lights given that its tires are found to be defective. P(DL | DT) = P(DL and DT) / P(DT) P(DL | DT) = 0.08 / 0.15 = 0.5333

  20. Problem 2 Elaine is enrolled in a self-paced course that allows three attempts to pass an exam on the material. She does not study and has probability 0.2 of passing on the first try. If she fails on the first try, her probability of passing on the second try increases to 0.3 because she learned something on the first attempt. If she fails on two attempts, the probability of passing on a third attempt is 0.4. She will stop as soon as she passes. The course rules force her to stop after three attempts in any case. Draw a tree diagram to illustrate what is described above, and use it to determine the probability that Elaine passes the exam.

  21. Problem 2 Solution 0.6 Failed 3 0.7 2 0.4 0.8 P 0.3 1 P 0.2 P P(passing) = 0.2 + 0.8  0.3 + 0.8  0.7  0.4 = 0.2 + 0.24 + 0.224 = 0.664

  22. Problem 3 A box contains 10 balls of the following types: 3 are red and dotted 2 are gray and dotted 1 is red and striped 4 are gray and striped If you randomly select one ball, what is the probability that the ball is • dotted? • dotted, given that it is red? • dotted or red? 5 / 10 3/ 4 6/ 10

  23. Problem 4 Among the patients at a mental health clinic, 35% suffer from depression and 40% suffer from anxiety. A total of 28% of the patients suffer from both conditions. (a) Display this information in a Venn Diagram. Use your Venn Diagram to determine what percent of the patients at this clinic …. • …suffer from depression but not anxiety. ________ • …suffer from neither depression nor anxiety. _____ Anxiety Depression 7% 28% 12% 7% 53%

  24. Problem 5 Two socks are selected at random and removed in succession (without replacement) from a drawer containing 6 brown socks and 4 blue socks. Let Y represent the number of brown socks selected. Give the probability distribution for Y: Y = Probability = Support your probabilities by a well labeled tree diagram below: 0 1 2 12/90 48/90 30/90 6/9 2 1 4/10 3/9 2 0 5/9 2 1 6/10 2 4/9

  25. Problem 6 The probability that a particular type of smoke detector will function properly and sound an alarm in the presence of smoke is 0.9. If there are two of these alarms in my home, what is the probability that at least one works in the presence of smoke? P(at least one) = 1 – P(none) = 1 – (0.1)(0.1) = 1 – 0.01 = 0.99

  26. Problem 7 A manufacturer of airplane parts knows from past experience that the probability is 0.8 that an order will be ready for shipment on time, the probability is 0.6 that an order will be delivered on time, and the probability is 0.5 that an order will be ready for shipment and will be delivered on time. (a) Find the probability that an order will be delivered on time, given that it is ready for shipment on time. (b) Find the probability that a randomly selected order will be ready for shipment on time or will be delivered on time. P(R) = 0.8 P(D) = 0.6 P(R and D) = 0.5 P(D|R) = P(D and R) / P(R) = 0.5 / 0.8 = .625 P(R or D) = P(R) + P(D) – P(R and D) = 0.8 + 0.6 – 0.5 = 0.9

  27. Problem 8 A box contains 20 fuses, 17 good and 3 defective. Two fuses are drawn from the box with replacement. • What is the probability that both fuses are defective? • What is the probability that one fuse is good and one is defective? (3/20)  (3/20) = 9/400 = 2.25% (17/20)  (3/20) = 51/400 = 12.75% (3/20)  (17/20) = 51/400 = 12.75% 25.5%

  28. Problem 9 A recent survey asked 100 randomly selected adult Americans if they thought that women should be allowed to go into combat situations. Here are the results: Gender Yes No Male 32 18 Female 8 42 (a) Find the probability of a “Yes” answer, given that the person was a female.  (b) Find the probability that the respondent was a male, given that the response was a “No.” P(Y | F) = 8 / 50 = 0.16 P(M | N) = 18 / 60 = 0.30

  29. Problem 10 Toss two balanced coins. Let A = head on the first toss, and let B = both tosses have the same outcome. Are events A and B independent? Explain your reasoning clearly. Yes they are independent. P(A) = ½ P(B) = ½ P(A and B) = P(A)*P(B) = ½ * ½ = ¼

  30. Problem 11 Parking for students at Central High School is very limited, and those who arrive late have to park illegally and take their chances at getting a ticket. Joey has determined that the probability that he has to park illegally and that he gets a parking ticket is 0.07. He recorded data last year and found that because of his perpetual tardiness, the probability that he will have to park illegally is 0.25. Suppose that Joey arrived late once again this morning and had to park in a no-parking zone. Can you find the probability that Joey will get a parking ticket? If so, do it. If you need additional information to find the probability, explain what is needed If T = Joey gets a parking ticket and I = Joey parked illegally then, P(T | I) = P(T and I) / P(I) = 0.07/ 0.25 = 0.28

  31. Problem 12 Two cards are dealt, one after the other, from a shuffled 52-card deck. Why is it wrong to say that the probability of getting two red cards is (1/2)(1/2) = 1/4? What is the correct probability of this event? It is wrong because the first card was not replaced and that change the probability of the second draw. P(both cards are red) = = P(1st card red) * P(2nd card is red | 1st card was red) = (26/52) * (25/51) = 0.2451

  32. Problem 1 QR Solution 0.55 Failed 3 0.65 2 0.45 0.75 P 0.35 1 P 0.25 P P(passing) = 0.25 + 0.75  0.35 + 0.75  0.65  0.45 = 0.25 + 0.2625 + 0.2194 = 0.7319

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