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Chapter 6 Probability in Statistics Active Learning Questions For use with classroom response systems Copyright © 2009 Pearson Education, Inc. Slide 6 - 1 An event is considered “significant” if its probability is less than or equal to 0.05. Is it significant to be dealt an ace when you are dealt one card from a standard 52-card deck? (There are four aces in the deck.) a. Yes b. No Slide 6 - 2 An event is considered “significant” if its probability is less than or equal to 0.05. Is it significant to be dealt an ace when you are dealt one card from a standard 52-card deck? (There are four aces in the deck.) a. Yes b. No Slide 6 - 3 An event is considered “significant” if its probability is less than or equal to 0.05. Muhammad Ali’s professional boxing record included 56 wins and 5 losses. If one match is selected at random, would it be considered significant if the match selected were a loss? a. Yes b. No Slide 6 - 4 An event is considered “significant” if its probability is less than or equal to 0.05. Muhammad Ali’s professional boxing record included 56 wins and 5 losses. If one match is selected at random, would it be considered significant if the match selected were a loss? a. Yes b. No Slide 6 - 5 The advertising for a cold remedy claimed that no other cold remedy acted faster. In an experiment to compare that remedy with another one, it did act faster on average, but the result was not significant. What does this mean? a. The difference was so small that it could have happened by chance even if the remedies were equivalent. b. The difference was so small that it could have happened by chance even if the remedies were not equivalent. c. The probability of the observed difference occurring by chance if the two remedies are equivalent was less than 0.05. d. The population mean response times are different, but the samples didn’t show it. Slide 6 - 6 The advertising for a cold remedy claimed that no other cold remedy acted faster. In an experiment to compare that remedy with another one, it did act faster on average, but the result was not significant. What does this mean? a. The difference was so small that it could have happened by chance even if the remedies were equivalent. b. The difference was so small that it could have happened by chance even if the remedies were not equivalent. c. The probability of the observed difference occurring by chance if the two remedies are equivalent was less than 0.05. d. The population mean response times are different, but the samples didn’t show it. Slide 6 - 7 A coin is tossed three times and HHT (heads, heads, tails) is observed. Is this result an outcome or an event? a. Outcome b. Event Slide 6 - 8 A coin is tossed three times and HHT (heads, heads, tails) is observed. Is this result an outcome or an event? a. Outcome b. Event Slide 6 - 9 Five electronic switches are tested at random from a day’s production and one is found to be defective. Is this observation an outcome or an event? a. Outcome b. Event Slide 6 - 10 Five electronic switches are tested at random from a day’s production and one is found to be defective. Is this observation an outcome or an event? a. Outcome b. Event Slide 6 - 11 If you flip a coin three times, the possible outcomes are HHH, HHT, HTH, THH, HTT, THT, TTH, TTT. What is the probability of getting at least one head and at least one tail? a. 2 0.6 3 c. 2 0.25 8 b. 1 0.50 2 d. 6 0.75 8 Slide 6 - 12 If you flip a coin three times, the possible outcomes are HHH, HHT, HTH, THH, HTT, THT, TTH, TTT. What is the probability of getting at least one head and at least one tail? a. 2 0.6 3 c. 2 0.25 8 b. 1 0.50 2 d. 6 0.75 8 Slide 6 - 13 From four men and two women, a committee is formed by drawing three names out of a hat. What is the probability that all three names drawn are those of men? a. 4 0.16 25 c. 4 0.2 20 b. 3 0.50 6 d. 3 0.15 20 Slide 6 - 14 From four men and two women, a committee is formed by drawing three names out of a hat. What is the probability that all three names drawn are those of men? a. 4 0.16 25 c. 4 0.2 20 b. 3 0.50 6 d. 3 0.15 20 Slide 6 - 15 A sample space has 5000 equally likely possible outcomes, what is the probability of each one? 1 a. 0.001 1000 1 c. 0.0002 5000 b. 2500 0.50 5000 d. 5000 1 5000 Slide 6 - 16 A sample space has 5000 equally likely possible outcomes, what is the probability of each one? 1 a. 0.001 1000 1 c. 0.0002 5000 b. 2500 0.50 5000 d. 5000 1 5000 Slide 6 - 17 A bag of marbles holds 5 red marbles, 6 green marbles and 14 blue marbles. IF one marble is drawn out, what is the probability that it is green? a. 5 0.2 25 c. 14 0.56 25 b. d. 6 0.24 25 6 0.3 20 Slide 6 - 18 A bag of marbles holds 5 red marbles, 6 green marbles and 14 blue marbles. IF one marble is drawn out, what is the probability that it is green? a. 5 0.2 25 c. 14 0.56 25 b. d. 6 0.24 25 6 0.3 20 Slide 6 - 19 A quarterback completes 67% of his passes, what is the probability that he will not complete his next pass? a. 0.67 b. 0.33 c. 0.23 d. 0.76 Slide 6 - 20 A quarterback completes 67% of his passes, what is the probability that he will not complete his next pass? a. 0.67 b. 0.33 c. 0.23 d. 0.76 Slide 6 - 21 Use the table to answer the question. If one person is selected to win a door prize, what is the probability he/she is not Danish? a. 37 0.153 242 c. 205 0.847 242 Nationality English Norwegian Danish German French Italian Frequency 42 73 37 26 13 51 b. 73 0.302 242 d. 169 0.698 242 Slide 6 - 22 Use the table to answer the question. If one person is selected to win a door prize, what is the probability he/she is not Danish? a. 37 0.153 242 c. 205 0.847 242 Nationality English Norwegian Danish German French Italian Frequency 42 73 37 26 13 51 b. 73 0.302 242 d. 169 0.698 242 Slide 6 - 23 In 2007, Ben Sheets’ record as a pitcher for the Milwaukee Brewers was 12 wins and 5 losses. In those 17 games he gave up the following number of hits: 2, 4, 8, 6, 4, 5, 4, 11, 7, 8, 6, 5, 6, 8, 6, 6, 6. Given that Ben Sheets wins or loses a game, estimate the probability that he gives up fewer than 6 hits. a. 6 0.353 17 11 0.647 17 b. c. 6 0.5 12 d. can’t determine Slide 6 - 24 In 2007, Ben Sheets’ record as a pitcher for the Milwaukee Brewers was 12 wins and 5 losses. In those 17 games he gave up the following number of hits: 2, 4, 8, 6, 4, 5, 4, 11, 7, 8, 6, 5, 6, 8, 6, 6, 6. Given that Ben Sheets wins or loses a game, estimate the probability that he gives up fewer than 6 hits. a. 6 0.353 17 11 0.647 17 b. c. 6 0.5 12 d. can’t determine Slide 6 - 25 A loaded die has the given probabilities. If you roll this die 630 times, how many times should you expect to see the number 3? Number 1 2 3 4 5 6 Probability 1/21 2/21 3/21 4/21 5/21 6/21 a. 1 630 30 21 2 630 60 21 b. c. 3 630 90 21 4 d. 630 120 21 Slide 6 - 26 A loaded die has the given probabilities. If you roll this die 630 times, how many times should you expect to see the number 3? Number 1 2 3 4 5 6 Probability 1/21 2/21 3/21 4/21 5/21 6/21 a. 1 630 30 21 2 630 60 21 b. c. 3 630 90 21 4 d. 630 120 21 Slide 6 - 27 Suppose you pay $2 to roll the die and win $6 if it comes up a 1 or 6, but nothing otherwise. What is your expected value? Number 1 2 3 4 5 6 Probability 1/21 2/21 3/21 4/21 5/21 6/21 a. $0 b. $0.67 c. $2 d. $6 Slide 6 - 28 Suppose you pay $2 to roll the die and win $6 if it comes up a 1 or 6, but nothing otherwise. What is your expected value? Number 1 2 3 4 5 6 Probability 1/21 2/21 3/21 4/21 5/21 6/21 a. $0 b. $0.67 c. $2 d. $6 Slide 6 - 29 In 2003, the U. S. death rate was 1.2 per 100,000 people due to motorcycle accidents. Motorcycles in the U. S. were involved in fatal crashes are the rate of 35.0 per 100 million miles drive. If the population of the U. S. is 300,000,000, what is the expected number of deaths due to motorcycle accidents? a. 1200 b. 2400 c. 3500 d. 3600 Slide 6 - 30 In 2003, the U. S. death rate was 1.2 per 100,000 people due to motorcycle accidents. Motorcycles in the U. S. were involved in fatal crashes are the rate of 35.0 per 100 million miles drive. If the population of the U. S. is 300,000,000, what is the expected number of deaths due to motorcycle accidents? a. 1200 b. 2400 c. 3500 d. 3600 Slide 6 - 31 Use the table to find what age a female of age 60 may expect to live on the average. Exact age 50 60 70 Female P(Death within Number of one year) Living 0.003240 95,378 0.007740 90,847 0.008938 80,583 a. 91.91 b. 83.21 c. 75.45 d. 85.45 Life Expectancy 31.91 23.21 15.45 Slide 6 - 32 Use the table to find what age a female of age 60 may expect to live on the average. Exact age 50 60 70 Female P(Death within Number of one year) Living 0.003240 95,378 0.007740 90,847 0.008938 80,583 a. 91.91 b. 83.21 c. 75.45 d. 85.45 Life Expectancy 31.91 23.21 15.45 Slide 6 - 33 Use the table to find how many 60-year old females on average will be living at age 61. Exact age 50 60 70 Female P(Death within Number of one year) Living 0.003240 95,378 0.007740 90,847 0.008938 80,583 Life Expectancy 31.91 23.21 15.45 a. 90,847 b. 80,583 c. 90,144 d. 90,062 Slide 6 - 34 Use the table to find how many 60-year old females on average will be living at age 61. Exact age 50 60 70 Female P(Death within Number of one year) Living 0.003240 95,378 0.007740 90,847 0.008938 80,583 Life Expectancy 31.91 23.21 15.45 a. 90,847 b. 80,583 c. 90,144 d. 90,062 Slide 6 - 35