nb a. a. a. a. a. b. a. p a. a.

53. a.

Exact: .212, .577, .573; Approximate: .211, .567, .596 b. Exact: .885, .575, .017; Approximate: .885, .579, .012 c. Exact: .002, .029, .617; Approximate: .003, .033, .599

55. a.

.9409 b. .9943

57. b.

Normal,

59. a.

1 b. 1 c. .982 d. .129

61. a.

.480, .667, .147 b. .050, 0

63. a.

short plan 1 better, whereas long plan 2 better

b. 65. a.

.238 b. .238 c. .313 d. .653 e. .653 f. .713

67. a.

.424 b. .567, c. 60 d. 66

69. a. b.

Exponential with c. Exponential with parameter

73. a.

.826, .826, .0636 b. .664 c. 172.727

77. a.

123.97, 117.373 b. .5517 c. .1587

79. a.

9.164, .385 b. .8790 c. .4247, skewness d. No, since P

81. a.

149.157, 223.595 b. .9573 c. .0414 d. 148.41 e. 9.57 f. 125.90

83. 85. b.

87. Yes, since the pattern in the plot is quite linear. 89. Yes 91. Yes 93. Plot lnx vs. z percentile. The pattern is straight, so a lognormal population distribution is plausible. 95. The pattern in the plot is quite linear; it is very plausible that strength is normally distributed. 97. There is substantial curvature in the plot. is a scale param- eter as is for the normal family. s l b a 1 b [⌫a 1 b ⌫ m 1 b][⌫a 1 b 1 m ⌫ b], a 5 b X , 17,000 5 .9332 nl l 5 .05 ¨ A i m | , 24 1l 5 15 1 E[h 1 X] 5 150, E[h 2 X] 5 138.51 1l 5 10 1 E[h 1 X] 5 100, E[h 2 X] 5 112.53 1 1 m 5 239, s 2 5 12.96

99. a.

for b. .259, .5, .241 c. 6, 43.2, 7.2 d. .518 e. 3.75

101. a.

for and for b. .917 c. 1.213

103. a.

.9162 b. .9549 c. 1.3374

105. a.

.3859 b. .0663 c. 72.97, 119.03

107. b.

for for , and for c. No.

d. 109. a.

.368, .828, .460 b. 352.53

c. d.

e. , mode

111. a. b.

No

c. d.

e. 113. b.

c. d.

e.

f. 115. a.

Lognormal b. 1 c. 2.72, .0185

119. a.

Exponential with c. Gamma with parameters and

121. a.

1365 3 b. 1365 2 c. .000002145

123. b.

Let be a sequence of observations from a Unif[0, 1] distribution a sequence of random numbers. Then with , the ’s are observa- tions from an exponential distribution with .

125. 127. a.

710, 84.423, .684 b. .376 g EX EgX l 5 10 x i x i 5 2.1ln1 2 u i u 1 , u 2 , u 3 , c cb a l 5 1 CV , 1 1, CV . 1 V X 5 2pl 2 1 1 21 2 pl 2 2 2 m 2 p l 1 1 1 2 pl 2 for x 0 p 1 2 exp 2l 1 x 1 1 2 p1 2 exp 2l 2 x n 2 2 a 2 1b m 5 150, m | 5 182.99 m 5 201.95 a 1b exp [2exp 2x 2 ab] exp 2x 2 ab Y | Bin10, 5 27 F 0 , .5 1 m | . 0 x . 2 5 1 2 1 x 2 x , 2 1, 5 4x 2 x 3 39 1 11 27 F x 5 0 1 x 7 3 5 7 4 2 3 4 x 0 x , 1 f x 5 x 2 0 y 12 F y 5 1 48 y 2 2 y 3 18

1. a.

.20 b. .42 c. At least one hose is in use at each pump; .70.

d. p

X x .16, .34, .50 for x 0, 1, 2, respectively; p Y y .24, .38, .38 for y 0, 1, 2, respec- tively; .50 e. No; p0, 0 ⬆ p X 0 ⭈ p Y

3. a.

.15 b. .40 c. .22 d. .17, .46

5. a.

.054 b. .00018

7. a.

.030 b. .120 c. .300 d. .380 e. Yes

9. a.

3380,000 b. .3024 c. .3593 d. 10Kx 2 ⫹ .05 for 20 x 30 e. No

11. a. ⭈ m

1 x ⭈ m 2 y xy

b. ⭈

[1 ⫹ m 1 ⫹ m 2 ]

c. ⭈

m 1 ⫹ m 2 m m; Poisson m 1 ⫹ m 2

13. a. e

⫺x ⫺ y for x 0, y 0 b. .400 c. .594 d. .330

15. a. F

y 1 ⫺ e ⫺ly ⫹ 1 ⫺ e ⫺ly 2 ⫺ 1 ⫺ e ⫺ly 3 for y 0 b. 23l

17. a.

.25 b. .318 c. .637 d. for ⫺R x R; no f X x 5 22R 2 2 x 2 pR 2 e 2 m 1 1 m 2 e 2m 1 2 m 2 e 2m 1 2 m 2 Chapter 5 Copyright 2010 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook andor eChapters. Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.