U EST I O N 1 3.9375 points Save Answer Exhibit 54A local bottling company has determined the number of machine breakdowns per month and their respective probabilities as shown below. Number of Breakdowns 0 1 2 3 4 Probability 0.07 0.38 0.25 0.18 0.12 3.9375 points Save Answer Refer to Exhibit 54. The probability of at least 3 breakdowns in a month is Q Use a TWO decimals format (i.e. 0.00) U EST I O N 2 Exhibit 54A local bottling company has determined the number of machine breakdowns per month and their respective probabilities as shown below. 3.9375 points Save Answer Number of Breakdowns 0 1 2 3 4 Probability 0.07 0.38 0.25 0.18 0.12 Refer to Exhibit 54. The expected number of machine breakdowns per month is Q Use a TWO decimals format (i.e. 0.00) U EST I O N 3 Exhibit 54A local bottling company has determined the number of machine breakdowns per month and their respective probabilities as shown below. Number of Breakdowns 0 1 2 3 4 Probability 0.07 0.38 0.25 0.18 0.12 3.9375 points Save Answer Refer to Exhibit 54. The probability of no breakdowns in a month is Q Use a TWO decimals format (i.e. 0.00) U EST I O N 4 Exhibit 510 Exhibit 510 The probability that Pete will catch fish on a particular day when he goes fishing is 0.7. Pete is going fishing 3 days next week. 3.9375 points Save Answer Refer to Exhibit 510. The probability that Pete will catch fish on exactly one day is 1. .008 2. .8 3. .189 4. Q U EST.096 ION 5 Exhibit 510 The probability that Pete will catch fish on a particular day when he goes fishing is 0.7. Pete is going fishing 3 days next week. 3.9375 points Save Answer Refer to Exhibit 510. The probability that Pete will catch fish on one day or less is 1. .096 2. .008 3. .216 4. Q U EST.104 ION 6 Exhibit 510 The probability that Pete will catch fish on a particular day when he goes fishing is 0.7. Pete is going fishing 3 days next week. 3.9375 points Save Answer Refer to Exhibit 510. The Standard Deviation of the number of days Pete will catch fish is 1. 2.4 2. .79 3. .48 4. Q U EST.16 ION 7 Exhibit 510 The probability that Pete will catch fish on a particular day when he goes fishing is 0.7. Pete is going fishing 3 days next week. 3.9375 points Saved Refer to Exhibit 510. The expected number of days Pete will catch fish is 1. 2.4 2. 2.1 3. 3 4. Q U EST1.6 ION 8 Exhibit 630 The time it takes a worker on an assembly line to complete a task is exponentially distributed with a mean of 8 minutes. 8 points Save Answer Refer to Exhibit 630. What is the probability density function for the time it takes to complete the task? 1. f(x) =(1/8 ) ex/8 for x 0 2. f(x) =(1/8 ) ex/8 for x 0 3. f(x) =(1/8 ) e8/x for x 0 4. None of the above Q U EST I O N 9 Exhibit 59Forty percent of all registered voters in a national election are female. A random sample of 6 voters is selected. 8 points Save Answer Refer to Exhibit 59. The probability that the sample contains exactly 2 female voters is Q Use four decimals format (i.e. 0.0000) U EST I O N 1 0 Exhibit 630 The time it takes a worker on an assembly line to complete a task is exponentially distributed with a mean of 8 minutes. 8 points Save Answer Refer to Exhibit 630. What is the probability that it will take a worker between 7 and 10 minutes to complete the task? The Probability is Q Use FOUR decimals format (i.e. 0.0000) U EST I O N 11 Exhibit 630 The time it takes a worker on an assembly line to complete a task is exponentially distributed with a mean of 8 minutes. 3.9375 points Save Answer Refer to Exhibit 630. What is the probability that it will take a worker 4 or less minutes to complete the task? The Probability is Q Use FOUR decimals format (i.e. 0.0000) U EST I O N 1 2 Exhibit 511 The random variable x is the number of occurrences of an event over an interval of ten minutes. It can be assumed that the probability of an occurrence is the same in any two time periods of an equal length. It is known that the mean number of occurrences in ten minutes is 5. 3.9375 points Save Answer Refer to Exhibit 511. The probability that there are 3 or less occurrences is 1. .0948 2. .2650 3. .1016 4. Q U EST.1239 ION 13 Exhibit 511 The random variable x is the number of occurrences of an event over an interval of ten minutes. It can be assumed that the probability of an occurrence is the same in any two time periods of an equal length. It is known that the mean number of occurrences in ten minutes is 5. 3.9375 points Save Answer Refer to Exhibit 511. The probability that there are 8 occurrences in ten minutes is 1. .0652 2. .9319 3. .0771 Q U EST.1126 ION 14 4. Exhibit 511 The random variable x is the number of occurrences of an event over an interval of ten minutes. It can be assumed that the probability of an occurrence is the same in any two time periods of an equal length. It is known that the mean number of occurrences in ten minutes is 5. 3.9375 points Save Answer Refer to Exhibit 511. The expected Variance of the random variable x is 1. 10 2. 5 3. 2.30 4. Q U EST2I O N 1 5 Four percent of the customers of a mortgage company default on their payments. A sample of five customers is selected. What is the probability that exactly two customers in the sample will default on their payments? The Probability is Use a FOUR decimals format (i.e. 0.0000) Q U EST I O N 1 6 3.9375 points Save Answer Exhibit 56Probability Distribution x 10 20 30 40 f(x) .1 .3 .4 .2 3.9375 points Save Answer Refer to Exhibit 56. The expected value of x equals Q Use a TWO decimals format (i.e. 00.00) U EST I O N 1 7 Exhibit 56Probability Distribution x 10 20 30 40 f(x) .1 .3 .4 .2 3.9375 points Save Answer Refer to Exhibit 56. The variance of x equals Q Use a TWO decimals format (i.e. 00.00) U EST I O N 1 8 Exhibit 66 The life expectancy of a particular brand of tire is normally distributed with a mean of 40,000 and a standard deviation of 5,000 miles. Refer to Exhibit 66. What is the probability that a randomly selected tire will have a life of at least 3.9375 points Save Answer 50,000 miles? 1. 0.4332 2. 0.0228 3. 0.0668 4. Q U EST0.9772 ION 19 Exhibit 66 The life expectancy of a particular brand of tire is normally distributed with a mean of 40,000 and a standard deviation of 5,000 miles. 3.9375 points Save Answer Refer to Exhibit 66. What is the random variable in this experiment? 1. the life expectancy of this brand of tire 2. the normal distribution 3. 40,000 miles 4. Q U ESTNone of the alternative answers are correct. ION 20 Exhibit 66 The life expectancy of a particular brand of tire is normally distributed with a mean of 40,000 and a standard deviation of 5,000 miles. 3.9375 points Save Answer Refer to Exhibit 66. What is the probability that a randomly selected tire will have a life of less than 30,000 miles? 1. 0.4772 2. 0.9772 3. 0.0228 4. Q U ESTNone of the alternative answers are correct. ION 21 Exhibit 66 The life expectancy of a particular brand of tire is normally distributed with a mean of 40,000 and a standard deviation of 5,000 miles. 3.9375 points Save Answer Refer to Exhibit 66. What is the probability that a randomly selected tire will have a life of exactly 47,500 miles? 1. 0.9332 2. 0.0668 3. zero 4. Q U EST0.4332 ION 22 Exhibit 66 The life expectancy of a particular brand of tire is normally distributed with a mean of 40,000 and a standard deviation of 5,000 miles. 3.9375 points Save Answer Refer to Exhibit 66. What percentage of tires will have a life of 35,000 to 45,000 miles? 1. 38.49% 2. 68.27% 3. 76.98% 4. Q U ESTNone of the alternative answers are correct. ION 23 Exhibit 58 The student body of a large university consists of 60% female students. A random sample of 8 students is selected. 3.9375 points Save Answer Refer to Exhibit 58. What is the probability that among the students in the sample at least 6 are male? 1. 0.0007 2. 0.0498 3. 0.0079 4. 0.0413 Q U EST I O N 2 4 Exhibit 58 The student body of a large university consists of 60% female students. A random sample of 8 students is selected. 3.9375 points Save Answer Refer to Exhibit 58. What is the probability that among the students in the sample at least 7 are female? 1. 0.8936 2. 0.0896 3. 0.0168 4. Q U EST0.1064 ION 25 Exhibit 58 The student body of a large university consists of 60% female students. A random sample of 8 students is selected. 3.9375 points Save Answer Refer to Exhibit 58. What is the probability that among the students in the sample exactly two are female? 1. 0.2936 2. 0.0007 3. 0.0413 4. Q U EST0.0896 ION 26 Exhibit 63 The weight of football players is normally distributed with a mean of 200 pounds and a standard deviation of 25 pounds. 3.9375 points Save Answer Refer to Exhibit 63. What is the maximum weight of the middle 90% of the players? 1. 158.8787 2. 258.8123 3. 241.1213 4. None of the alternative answers are correct. Q U EST I O N 2 7 Q U EST I O N 2 7 Exhibit 63 The weight of football players is normally distributed with a mean of 200 pounds and a standard deviation of 25 pounds. 3.9375 points Save Answer Refer to Exhibit 63. What percent of players weigh between 170 and 230 pounds? 1. 34.13% 2. 68.26% 3. 76.99% 4. Q U ESTNone of the alternative answers are correct. ION 28 Exhibit 63 The weight of football players is normally distributed with a mean of 200 pounds and a standard deviation of 25 pounds. 3.9375 points Save Answer Refer to Exhibit 63. What is the random variable in this experiment? 1. the weight of football players 2. the normal distribution 3. 25 pounds 4. Q U EST200 pounds ION 29 Exhibit 63 The weight of football players is normally distributed with a mean of 200 pounds and a standard deviation of 25 pounds. 3.9375 points Save Answer Refer to Exhibit 63. The probability of a player weighing less than 240 pounds is 1. 0.9452 2. 0.0548 3. 0.4772 4. Q U EST0.0728 ION 30 Exhibit 63 The weight of football players is normally distributed with a mean of 200 pounds and a standard deviation of 25 pounds. 3.9375 points Save Answer Refer to Exhibit 63. The probability of a player weighing more than 231.90 pounds is 1. 0.0495 2. 0.1010 3. 0.8990 4. Q U EST0.4505 ION 31 Exhibit 65 The weight of items produced by a machine is normally distributed with a mean of 8 ounces and a standard deviation of 2 ounces. 3.9375 points Save Answer Refer to Exhibit 65. What is the probability that a randomly selected item weighs exactly 9 ounces? The Probability is Use FOUR decimals format (i.e. 0.0000) Q U EST I O N 3 2 . Q U EST I O N 3 2 Exhibit 65 3.9375 points Save Answer The weight of items produced by a machine is normally distributed with a mean of 8 ounces and a standard deviation of 2 ounces. Refer to Exhibit 65. What percentage of items will weigh at least 9 ounces? The Percentage is Q Use TWO decimals format (i.e. 00.00) U EST I O N 3 3 % Exhibit 65 The weight of items produced by a machine is normally distributed with a mean of 8 ounces and a standard deviation of 2 ounces. 3.9375 points Save Answer Refer to Exhibit 65. What is the probability that a randomly selected item will weigh between 8 and 12 ounces? The Probability is Use FOUR decimals format (i.e. 0.0000) Q U EST I O N 3 4 Exhibit 65 The weight of items produced by a machine is normally distributed with a mean of 8 ounces and a standard deviation of 2 ounces. Refer to Exhibit 65. What is the probability that a randomly selected item will weigh more than 12 ounces? The Probability is Q Use FOUR decimals format (i.e. 0.0000) U EST I O N 3 5 Exhibit 65 The weight of items produced by a machine is normally distributed with a mean of 8 ounces and a standard deviation of 2 ounces. Refer to Exhibit 65. What is the minimum weight of the middle 95% of the items? The weight is Use FOUR decimals format (i.e. 0.0000) ounces