ch06

CHAPTER SIX

Continuous Distributions

D 1. Which of the following is NOT a continuous distribution?

E A. normal distributionTerm B. exponential distribution

C. uniform distributionD. binomial distribution

D 2. The uniform distribution is _______________.

E A. bimodalTerm B. skewed to the right

C. skewed to the leftD. symmetric

173

174 Test Bank

A 3. The uniform distribution is also known as the __________.

E A. rectangular distributionTerm B. gamma distribution

C. beta distributionD. Erlang distribution

D 4. The distribution in the following graph is a ________ distribution.

E A. normalTerm B. gamma

C. exponentialD. uniform

A 5. The distribution in the following graph is a ________ distribution.



0.00

0.01

0.02

0.03

0.04

0.05

0.06

35 40 45 50 55 60 65x

f(X

)

0

0.1

0.2

0.3

0.4

0.5

x

Chapter 6: Continuous Distributions 175

C 6. The distribution in the following graph is a ________ distribution.



B 7. If x is uniformly distributed over the interval 8 to 12, inclusively (8 £ x £ 12), then the height of this distribution, f(x), is __________________.

E A. 1/8Term B. 1/4

C. 1/12D. 1/20

A 8. If x is uniformly distributed over the interval 8 to 12, inclusively (8 £ x £ 12), then the mean() of this distribution is __________________.

M A. 10Calc B. 20

C. 5D. incalculable

C 9. If x is uniformly distributed over the interval 8 to 12, inclusively (8 £ x £ 12), then the standard deviation () of this distribution is __________________.

M A. 4Calc B. 1.33

C. 1.15D. 2

0.0

0.2

0.4

0.6

0.8

1.0

1.2

0 1 2 3 4 5 6x

176 Test Bank

B 10. If x is uniformly distributed over the interval 8 to 12, inclusively (8 £ x £ 12), then the P(9 £ x £ 11) is __________________.

M A. 0.250Calc B. 0.500

C. 0.333D. 1.000

C 11. If x is uniformly distributed over the interval 8 to 12, inclusively (8 £ x £ 12), then the P(10.0 £ x £ 11.5) is __________________.

M A. 0.250Calc B. 0.333

C. 0.375D. 0.000

D 12. If x is uniformly distributed over the interval 8 to 12, inclusively (8 £ x £ 12), then the P(13 £ x £ 15) is __________________.

M A. 0.250Calc B. 0.500

C. 0.375D. 0.000

B 13. If x is uniformly distributed over the interval 8 to 12, inclusively (8 £ x £ 12), then P(x < 7) is __________________.

M A. 0.500Calc B. 0.000

C. 0.375D. 0.250

A 14. If x is uniformly distributed over the interval 8 to 12, inclusively (8 £ x £ 12), then P(x £ 11) is __________________.

M A. 0.750Calc B. 0.000

C. 0.333D. 0.500


D 15. If x is uniformly distributed over the interval 8 to 12, inclusively (8 £ x £ 12), then P(x ³ 10) is __________________.

E A. 0.750Calc B. 0.000

C. 0.333D. 0.500

A 16. If x is uniformly distributed over the interval 20 to 30, inclusively (20 £ x £ 30), then the height of this distribution, f(x), is __________________.

E A. 1/10Calc B. 1/20

C. 1/30D. 1/50

B 17. If x is uniformly distributed over the interval 20 to 30, inclusively (20 £ x £ 30), then the mean () of this distribution is __________________.

M A. 50Calc B. 25

C. 10D. 5

D 18. If x is uniformly distributed over the interval 20 to 30, inclusively (20 £ x £ 30), then the standard deviation () of this distribution is __________________.

M A. incalculableCalc B. 8.33

C. 0.833D. 2.89

C 19. If x is uniformly distributed over the interval 20 to 30, inclusively (20 £ x £ 30), then P(25 £ x £ 28) is __________________.

M A. 0.250Calc B. 0.500

C. 0.300D. 1.000

178 Test Bank

A 20. If x is uniformly distributed over the interval 20 to 30, inclusively (20 £ x £ 30), then P(21.75 £ x £ 24.25) is __________________.

M A. 0.250Calc B. 0.333

C. 0.375D. 0.000

B 21. If x is uniformly distributed over the interval 20 to 30, inclusively (20 £ x £ 30), then P(33 £ x £ 35) is __________________.

M A. 0.500Calc B. 0.000

C. 0.375D. 0.200

C 22. If x is uniformly distributed over the interval 20 to 30, inclusively (20 £ x £ 30), then P(x < 17) is __________________.

M A. 0.500Calc B. 0.300

C. 0.000D. 0.250

A 23. If x is uniformly distributed over the interval 20 to 30, inclusively (20 £ x £ 30), then P(x £ 22) is __________________.

M A. 0.200Calc B. 0.300

C. 0.000D. 0.250

D 24. If x is uniformly distributed over the interval 20 to 30, inclusively (20 £ x £ 30), then P(x ³ 24) is __________________.

M A. 0.100Calc B. 0.000

C. 0.333D. 0.600


C 25. Helen Casner, a labor relations arbitrator, feels that the amount of time needed to arbitrate a labor dispute is uniformly distributed over the interval 4 to 24 hours, inclusively (4 £ x £ 24). Accordingly, the mean (average) time needed to arbitrate a labor dispute is ____________.

M A. 20 hoursBCalc B. 16 hours

C. 14 hoursD. 12 hours

D 26. Helen Casner, a labor relations arbitrator, feels that the amount of time needed to arbitrate a labor dispute is uniformly distributed over the interval 4 to 24 hours, inclusively (4 £ x £ 24). Accordingly, the probability that a labor dispute will be arbitrated in 8 hours or less is ____________.

M A. 0.3333BCalc B. 0.6667

C. 0.0000D. 0.2000

C 27. Helen Casner, a labor relations arbitrator, feels that the amount of time needed to arbitrate a labor dispute is uniformly distributed over the interval 4 to 24 hours, inclusively (4 £ x £ 24). Accordingly, the probability that a labor dispute will require between 8 and 16 hours, inclusively, for arbitration is ____________.

M A. 0.3333BCalc B. 0.6667

C. 0.4000D. 0.2000

B 28. The normal distribution is an example of _______.

E A. a discrete distributionTerm B. a continuous distribution

C. a bimodal distributionD. an exponential distribution

180 Test Bank

B 29. The total area underneath any normal curve is _______.

E A. equal to the meanTerm B. equal to 1

C. equal to the varianceD. equal to the coefficient of variation

D 30. The area to the left of the mean in any normal distribution is _______.

E A. equal to the meanTerm B. equal to 1

C. equal to the varianceD. equal to 0.5

B 31. For any normal distribution, any value less than the mean would have a _______.

E A. positive z-score Term B. negative z-score

C. negative varianceD. negative probability of occurring

D 32. A standardized normal distribution has the following characteristics:

E A. the mean and variance are both equal to 1Term B. the mean and variance are both equal to 0

C. the mean is equal to the varianceD. the mean is equal to 0 and the variance is equal to 1

C 33. If x is a normal random variable with mean 80 and standard deviation 5, calculate the z score if x=88.

E A. 1.8Calc B. -1.8

C. 1.6D. -1.6

D 34. If x is a normal random variable with mean 80 and standard deviation 5, calculate the z score if x=72.

E A. 1.8Calc B. -1.8

C. 1.6D. -1.6


D 35. If x is a normal random variable with mean 80 and standard deviation 5, calculate the z score if x=92.

E A. 2.1Calc B. 12

C. 1.2D. 2.4

C 36. If x is a normal random variable with mean 60 and standard deviation 2, calculate the z score if x=57.

E A. 1.5Calc B. 2.5

C. -1.5D. -2.5

C 37. Suppose x is a normal random variable with mean 60 and standard deviation 2. A z score was calculated for a number, and the z score is 3.4. What is x?

M A. 63.4Calc B. 56.6

C. 66.8D. 53.2

D 38. Suppose x is a normal random variable with mean 60 and standard deviation 2. A z score was calculated for a number, and the z score is -1.3. What is x?

M A. 58.7Calc B. 61.3

C. 62.6D. 57.4

B 39. Let z be a normal random variable with mean 0 and standard deviation 1. Use the normal tables to find P(z < 1.3).

E A. 0.4032Calc B. 0.9032

C. 0.0968D. 0.3485

182 Test Bank

D 40. Let z be a normal random variable with mean 0 and standard deviation 1. Use the normal tables to find P(1.3 < z < 2.3).

E A. 0.4032Calc B. 0.9032

C. 0.4893D. 0.0861

C 41. Let z be a normal random variable with mean 0 and standard deviation 1. Use the normal tables to find P(z > 2.4).

M A. 0.4918Calc B. 0.9918

C. 0.0082D. 0.4793

D 42. Let z be a normal random variable with mean 0 and standard deviation 1. Use the normal tables to find P(z < -2.1).

M A. 0.4821Calc B. -0.4821

C. 0.9821D. 0.0179

B 43. Let z be a normal random variable with mean 0 and standard deviation 1. Use the normal tables to find P(z > -1.1).

M A. 0.3643Calc B. 0.8643

C. 0.1357D. -0.1357

C 44. Let z be a normal random variable with mean 0 and standard deviation 1. Use the normal tables to find P(-2.25 < z < -1.1).

M A. 0.3643Calc B. 0.8643

C. 0.1235D. 0.4878


B 45. Let z be a normal random variable with mean 0 and standard deviation 1. Use the normal tables to find P(-2.25 < z < 1.1).

M A. 0.3643Calc B. 0.8521

C. 0.1235D. 0.4878

C 46. Let z be a normal random variable with mean 0 and standard deviation 1. The 50th

percentile of z is ____________.

E A. 0.670Calc B. -1.254

C. 0.000D. 1.280

A 47. Let z be a normal random variable with mean 0 and standard deviation 1. The 75th


M A. 0.670Calc B. -1.254

C. 0.000D. 1.280

D 48. Let z be a normal random variable with mean 0 and standard deviation 1. The 90th


M A. 1.645Calc B. -1.254

C. 1.960D. 1.280

A 49. Let z be a normal random variable with mean 0 and standard deviation 1. The 95th


M A. 1.645Calc B. -1.254

C. 1.960D. 1.280

184 Test Bank

B 50. Let x be a normal random variable with mean 20 and standard deviation 4. Find P(x < 25).

M A. 0.3944Calc B. 0.8944

C. 0.1056D. 0.6056

C 51. Let x be a normal random variable with mean 20 and standard deviation 4. Find P(x < 17).

M A. 0.2734Calc B. 0.7734

C. 0.2266D. -0.2734


M A. 0.0987Calc B. 0.4013

C. -0.0987D. 0.5987

D 53. Let x be a normal random variable with mean 20 and standard deviation 4. Find P(16 < x < 22).

M A. 0.4672Calc B. 0.0328

C. 0.1498D. 0.5328

B 54. Let x be a normal random variable with mean 20 and standard deviation 4. The 50th percentile of x is ____________.

E A. 4.000Calc B. 20.000

C. 22.698D. 26.579


C 55. Let x be a normal random variable with mean 20 and standard deviation 4. The 75th percentile of x is ____________.

M A. 25.126Calc B. 20.000

C. 22.698D. 26.579

A 56. Let x be a normal random variable with mean 20 and standard deviation 4. The 90th percentile of x is ____________.

M A. 25.126Calc B. 20.000

C. 22.698D. 26.579

D 57. Let x be a normal random variable with mean 20 and standard deviation 4. The 95th percentile of x is ____________.

M A. 25.126Calc B. 20.000

C. 22.698D. 26.579

D 58. Let x be a normal random variable with mean 40 and standard deviation 8. Find P(32 < x < 44).

M A. 0.4672Calc B. 0.0328

C. 0.1498D. 0.5328

A 59. Let x be a normal random variable with mean 40 and standard deviation 8. Find P(x < 96).

M A. 1.0000Calc B. 0.0000

C. 0.0793D. 0.0575

186 Test Bank


M A. 1.0000Calc B. 0.0000

C. 0.2580D. 0.0472

B 61. A z score is the number of __________ that a value is from the mean.

E A. variancesTerm B. standard deviations

C. unitsD. miles

C 62. Within a range of z scores from -1 to +1, you can expect to find _______ per cent of the values in a normal distribution.

E A. 95Term B. 99

C. 68D. 34

A 63. Within a range of z scores from -2 to +2, you can expect to find _______ per cent of the values in a normal distribution.

E A. 95Term B. 99

C. 68D. 34

C 64. The expected (mean) life of a particular type of light bulb is 1,000 hours with a standard deviation of 50 hours. The life of this bulb is normally distributed. What is the probability that a randomly selected bulb would last longer than 1150 hours?

M A. 0.4987Calc B. 0.9987

C. 0.0013D. 0.5013


B 65. The expected (mean) life of a particular type of light bulb is 1,000 hours with a standard deviation of 50 hours. The life of this bulb is normally distributed. What is the probability that a randomly selected bulb would last fewer than 1100 hours?

M A. 0.4772Calc B. 0.9772

C. 0.0228D. 0.5228

C 66. The expected (mean) life of a particular type of light bulb is 1,000 hours with a standard deviation of 50 hours. The life of this bulb is normally distributed. What is the probability that a randomly selected bulb would last fewer than 940 hours?

M A. 0.3849Calc B. 0.8849

C. 0.1151D. 0.6151

D 67. Suppose you are working with a data set that is normally distributed with a mean of 400 and a standard deviation of 20. Determine the value of x such that 60% of the values are greater than x.

H A. 404.5Calc B. 395.5

C. 405.0D. 395.0

A 68. Suppose you are working with a data set that is normally distributed with a mean of 400 and a standard deviation of 20. Determine the value of x such that only 1% of the values are greater than x.

H A. 446.6Calc B. 353.4

C. 400.039D. 405

188 Test Bank

C 69. Suppose you are working with a data set that is normally distributed with a mean of 400 and a standard deviation of 20. Determine the value of x such that 5% of the values are less than x.

H A. 432.9Calc B. 396

C. 367.1D. 404

C 70. The E.P.A. has reported that the average fuel cost for a particular type of automobile is $800 with a standard deviation of $80. Fuel cost is assumed to be normally distributed. If one of these cars is randomly selected, what is the probability that the fuel cost for this car exceeds $900?

M A. 0.3944Calc B. 0.8944

C. 0.1056D. 0.6056

B 71. The E.P.A. has reported that the average fuel cost for a particular type of automobile is $800 with a standard deviation of $80. Fuel cost is assumed to be normally distributed. If one of these cars is randomly selected, what is the probability that the fuel cost for this car exceeds $760?

M A. 0.1915Calc B. 0.6915

C. 0.3085D. 0.8085

B 72. The E.P.A. has reported that the average fuel cost for a particular type of automobile is $800 with a standard deviation of $80. Fuel cost is assumed to be normally distributed. We would expect that only 10% of these cars would have an annual fuel cost greater than _______.

H A. 820.0Calc B. 902.4

C. 808.0D. 812.8


A 73. The E.P.A. has reported that the average fuel cost for a particular type of automobile is $800 with a standard deviation of $80. Fuel cost is assumed to be normally distributed. If a car is randomly selected, what is the probability that fuel cost would be between $700 and $900?

M A. 0.7888Calc B. 0.8944

C. 0.3944D. 0.1056

C 74. The net profit of an investment is normally distributed with a mean of $10,000 and a standard deviation of $5,000. The probability that the investor will not have a net loss is _____________.

M A. 0.4772BCalc B. 0.0228

C. 0.9772D. 0.9544

B 75. The net profit of an investment is normally distributed with a mean of $10,000 and a standard deviation of $5,000. The probability that the investor will have a net loss is _____________.

M A. 0.4772BCalc B. 0.0228

C. 0.9772D. 0.9544

A 76. The net profit of an investment is normally distributed with a mean of $10,000 and a standard deviation of $5,000. The probability that the investor’s net profit will be between $12,000 and $15,000 is _____________.

M A. 0.1859BCalc B. 0.3413

C. 0.8413D. 0.4967

190 Test Bank

C 77. The net profit of an investment is normally distributed with a mean of $10,000 and a standard deviation of $5,000. The probability that the investor’s net gain will be at least $5,000 is _____________.

M A. 0.1859BCalc B. 0.3413

C. 0.8413D. 0.4967

A 78. Completion time (from start to finish) of a building remodeling project is normally distributed with a mean of 200 work-days and a standard deviation of 10 work-days. The probability that the project will be completed within 185 work-days is ______.

M A. 0.0668BCalc B. 0.4332

C. 0.5000D. 0.9332

D 79. Completion time (from start to finish) of a building remodeling project is normally distributed with a mean of 200 work-days and a standard deviation of 10 work-days. The probability that the project will be completed within 215 work-days is _____.

M A. 0.0668BCalc B. 0.4332

C. 0.5000D. 0.9332

A 80. Completion time (from start to finish) of a building remodeling project is normally distributed with a mean of 200 work-days and a standard deviation of 10 work-days. The probability that the project will not be completed within 215 work-days is _____.

M A. 0.0668BCalc B. 0.4332

C. 0.5000D. 0.9332


C 81. Completion time (from start to finish) of a building remodeling project is normally distributed with a mean of 200 work-days and a standard deviation of 10 work-days. The probability that the project will be completed within ____ work-days is 0.99.

M A. 211BCalc B. 187

C. 223D. 200

B 82. The length of steel rods produced by a shearing process are normally distributed with = 120 inches and = 0.05 inch. Industry standards require the rods to be between 119.90 and 120.15 inches, inclusively. The probability that a rod produced by this process will conform to industry standards is ______________.

M A. 0.9542BCalc B. 0.9759

C. 0.9974D. 0.6826

C 83. The length of steel rods produced by a shearing process are normally distributed with = 120 inches and = 0.05 inch. Industry standards require the rods to be between 119.90 and 120.15 inches, inclusively. Any rod longer than 120.15 inches is re-sheared. The probability that a rod produced by this process will require re-shearing is ___________.

M A. 0.0458BCalc B. 0.0228

C. 0.0013D. 0.0241

B 84. The length of steel rods produced by a shearing process are normally distributed with = 120 inches and = 0.05 inch. Industry standards require the rods to be between 119.90 and 120.15 inches, inclusively. Any rod shorter than 119.90 inches is scrapped (used in the next melt). The probability that a rod produced by this process will be scrapped is ___________.

M A. 0.0458BCalc B. 0.0228

C. 0.0013D. 0.0241

192 Test Bank

A 85. The weights of aluminum castings produced by a process are normally distributed with = 2 pounds and = 0.10 pound. Design specifications require the castings to weigh between 1.836 and 2.164 pounds, inclusively. The probability that a casting produced by this process will conform to design specifications is _________.

M A. 0.8990BCalc B. 0.4495

C. 0.9974D. 0.9500

C 86. The weights of aluminum castings produced by a process are normally distributed with = 2 pounds and = 0.10 pound. Design specifications require the castings to weigh between 1.836 and 2.164 pounds, inclusively. Any casting weighing less than 1.836 pounds is scrapped. The probability that a casting produced by this process will be scrapped, due to under-weight, is _________.

M A. 0.1010BCalc B. 0.4495

C. 0.0505D. 0.0010

C 87. The weights of aluminum castings produced by a process are normally distributed with = 2 pounds and = 0.10 pound. Design specifications require the castings to weigh between 1.836 and 2.164 pounds, inclusively. Any casting weighing more than 2.164 pounds is re-worked. The probability that a casting produced by this process will be re-worked, due to over-weight, is _________.

M A. 0.0010BCalc B. 0.1010

C. 0.0101D. 0.0505

B 88. Let x be a binomial random variable with n=20 and p=.8. If we use the normal distribution to approximate probabilities for this, we would use a mean of _______.

E A. 20Calc B. 16

C. 3.2D. 8


C 89. Let x be a binomial random variable with n=20 and p=.8. If we use the normal distribution to approximate probabilities for this, we would use a standard deviation of _______.

M A. 16Calc B. 3.2

C. 1.79D. 0.16

B 90. Let x be a binomial random variable with n=20 and p=.8. If we use the normal distribution to approximate probabilities for this, a correction for continuity should be made. To find the probability of more than 12 successes, we should find _______.

M A. P(x>12)Term B. P(x>12.5)

C. P(x>11.5)D. P(x<11.5)

B 91. Let x be a binomial random variable with n=20 and p=.8. If we use the normal distribution to approximate probabilities for this, a correction for continuity should be made. To find the probability of 12 successes or more, we should find _______.

M A. P(x>12)Term B. P(x>11.5)

C. P(x>12.5)D. P(x<12.5)

C 92. Let x be a binomial random variable with n=20 and p=.8. If we use the normal distribution to approximate probabilities for this, a correction for continuity should be made. To find the probability of more than 6 but less than 12 successes, we should find _______.

H A. P(6<x<12)Calc B. P(6.5<x<12.5)

C. P(6.5<x<11.5)D. P(5.5<x<12.5)

194 Test Bank

C 93. Ten percent of all personal loans granted by First Easy Money Bank are defaulted in the fourth re-payment month. One-hundred four-month old personal loans are randomly selected from a population of 3,000. The number of defaulted loans in this sample has a binomial distribution. If we use the normal distribution to approximate probabilities for this, we would use a mean of _______.

M A. 30BCalc B. 50

C. 10D. 300

B 94. According to the U. S. Department of Commerce, 8.6% of the total civilian employment in Washington state is related to manufactured exports. A sample of 200 civilian employees in Washington state is randomly selected. If x is the number of employees in the sample with jobs related to manufactured exports, then the mean (expected) value of x is _______________.

M A. 8.60BCalc B. 17.20

C. 15.72D. 3.96

D 95. According to the U. S. Department of Commerce, 8.6% of the total civilian employment in Washington state is related to manufactured exports. A sample of 200 civilian employees in Washington state is randomly selected. If x is the number of employees in the sample with jobs related to manufactured exports, then the standard deviation of x is _______________.

H A. 8.60Calc B. 17.20

C. 15.72D. 3.96

D 96. According to the U. S. Department of Commerce, 8.6% of the total civilian employment in Washington state is related to manufactured exports. A sample of 200 civilian employees in Washington state is randomly selected. The probability that between 9 and 15 (inclusively) of the employees have jobs related to manufactured exports is _______________.

H A. 0.9564BCalc B. 0.9435

C. 0.9386D. 0.9874


B 97. The exponential distribution is an example of _______.

E A. a discrete distributionTerm B. a continuous distribution

C. a bimodal distributionD. an normal distribution

B 98. If arrivals at a bank follow a Poisson distribution, then the time between arrivals would be _______.

M A. normally distributedTerm B. exponentially distributed

C. a binomial distributionD. equal to lambda

B 99. For an exponential distribution with lambda () equal to 4 per minute, the mean () is __________.

E A. 4Term B. 0.25

C. 0.5D. 1

C 100. For an exponential distribution with lambda () equal to 4 per minute, the standard deviation () is _______.

M A. 4Term B. 0.5

C. 0.25D. 1

A 101. The average time between phone calls is 30 seconds. Assuming that the time between calls is exponentially distributed, find the probability that more than a minute elapses between calls.

M A. 0.135Calc B. 0.368

C. 0.865D. 0.607

196 Test Bank

D 102. The average time between phone calls is 30 seconds. Assuming that the time between calls is exponentially distributed, find the probability that less than two minutes elapse between calls.

M A. 0.018Calc B. 0.064

C. 0.936D. 0.982

B 103. Suppose that the mean time between arrivals is ten minutes and that random arrivals are Poisson distributed. Find the probability that less than 8 minutes pass between two arrivals.

M A. 0.449Calc B. 0.551

C. 0.286D. 0.714

A 104. Suppose that the mean time between arrivals is ten minutes and that random arrivals are Poisson distributed. Find the probability that more than 5 minutes pass between two arrivals.

M A. 0.607Calc B. 0.393

C. 0.135D. 0.865

D 105. On Saturdays, cars arrive at Sami Schmitt's Scrub and Shine Car Wash at the rate of 6 cars per fifteen minute interval. The average interarrival time between cars is _____________.

E A. 2.167 minutesBCalc B. 10.000 minutes

C. 0.167 minutesD. 2.500 minutes


B 106. On Saturdays, cars arrive at Sami Schmitt's Scrub and Shine Car Wash at the rate of 6 cars per fifteen minute interval. The probability that at least 2 minutes will elapse between car arrivals is _____________.

M A. 0.0000BCalc B. 0.4493

C. 0.1353D. 2.2255

C 107. On Saturdays, cars arrive at Sami Schmitt's Scrub and Shine Car Wash at the rate of 6 cars per fifteen minute interval. The probability that at least 5 minutes will elapse between car arrivals is _____________.

M A. 0.0000BCalc B. 0.4493

C. 0.1353D. 0.0067

B 108. On Saturdays, cars arrive at Sami Schmitt's Scrub and Shine Car Wash at the rate of 6 cars per fifteen minute interval. The probability that less than 10 minutes will elapse between car arrivals is _____________.

M A. 0.8465BCalc B. 0.9817

C. 0.0183D. 0.1535

D 109. The exponential distribution is _______.

E A. symmetricTerm B. bimodal

C. skewed to the leftD. skewed to the right

B 110. The standard normal distribution is also called _______.

E A. an exponential distributionTerm B. the z distribution

C. a discrete distributionD. a finite distribution

198 Test Bank

A 111. The normal distribution is also referred to as _______.

E A. the Gaussian distributionTerm B. the de Moivre distribution

C. the exponential distributionD. the Poisson distribution

112. Richard Bowman, Purchasing Manager at Mid-West Medical Center, is reviewing the annual vendor performance report. Richard is searching for opportunities to reduce Mid-West's inventory costs, and pauses to study a table summarizing the delivery times (elapsed time from placing an order until the material is received) for two suppliers of surgical dressings and related materials.

Medco Supplies Gauze-R-US (days) 17 9 (days) 5 2

Discuss the relevance of this information to Richard's objective of reducing inventory costs. Which vendor should Mid-West favor? Why? What other factors should Richard consider?

M _________________________________________________________________ BApp _________________________________________________________________

_________________________________________________________________ _________________________________________________________________ _________________________________________________________________ _________________________________________________________________ _________________________________________________________________ _________________________________________________________________ _________________________________________________________________ _________________________________________________________________


113. Candace Maldonado, VP of Customer Services at Alamo Auto Insurance, Inc., is reviewing the performance of the claims processing division of her company. Her staff reports that the time required to process claims is normally distributed with = 14 days and = 3 days. Even though Candace has received several complaint letters from customers alleging lengthy delays in claims processing, she knows that Alamo out-performs the industry. (For the industry, processing time is normal with = 25 days and = 5 days.) Moreover, she knows that improving (decreasing) claims processing time will reduce investment interest earned by the company -- putting a downward pressure on corporate profits and an upward pressure on premiums.

Discuss Candace's dilemma. How should she respond to the complaining customers? Should she share her statistics with other corporate managers?

M _________________________________________________________________ BApp _________________________________________________________________

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200 Test Bank

114. Mone Carlo Simulation analysis of a proposed capital expenditure indicates that the net present value of the project is normallly distributed with of $6,000 and a of $4,000.

Discuss the risk and profitability aspects of the proposed capital expenditure.MBApp

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($10,000) ($5,000) $0 $5,000 $10,000 $15,000 $20,000

Net Present Value (x)

f(x

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115. Monette Construction, Inc. is preparing to bid on a major roadway construction project. PERT analysis indicates that project time is normallly distributed with a of 600 day and a of 20 days. The Request for Bids states that the project must be complete within 635 days. The winner of the bid will be assess a penalty of $1,000 per day for each day the project extends beyond 635 days.

Discuss the risks to Monette Construction assuming it wins the bid.MBApp

Discuss the risk and profitability aspects of the proposed capital expenditure.

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500 525 550 575 600 625 650 675 700

Project Time (days)

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202 Test Bank

ch06

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