1. ____ is a property of a point estimator that is present when the expected value of the point estimator is equal to the population parameter it estimates A. .0495

2. 400 registered voters were randomly selected asked whether gun laws should be changed. 300 said yes and 100 said no.
The point estimate of the proportion in the population who will respond yes is A. .75

3. A _______________ sample is used when members of the population are chosen to become part of the sample because they are easily accessible. A. convenience

4. A doctor would like to determine if there is a difference between the blood pressure of people who walk every day for 60 minutes and those who walk one day per week for 60 minutes. Fifty of her patients who report that they have routinely walked 60 minutes every day for the past two years and 50 who report that they have walked 60 minutes only one day per week will be identified. The doctor will examine their medical records and collect their blood pressure readings over this two-year period. This is an example of a(n): A. observational study.

5. A finite population correction factor is needed in computing the standard deviation of the sampling distribution of sample means _____. A. whenever the sample size is more than 5% of the population size

6. A finite population correction factor is needed in computing the standard deviation of the sampling distribution of sample means _____. A. whenever the sample size is more than 5% of the population size

7. A manufacturer of power tools claims that the mean amount of time required to assemble their top-of-the-line table saw is 80 minutes with a standard deviation of 40 minutes. Suppose a random sample of 64 purchasers of this table saw is taken. The mean of the sampling distribution of the sample mean is __________ minutes. A. 80

8. A manufacturer of power tools claims that the mean amount of time required to assemble their top-of-the-line table saw is 80 minutes with a standard deviation of 40 minutes. Suppose a random sample of 64 purchasers of this table saw is taken. The standard deviation of the sampling distribution of the sample mean is __________ minutes. A. 5

9. A manufacturer of power tools claims that the mean amount of time required to assemble their top-of-the-line table saw is 80 minutes with a standard deviation of 40 minutes. Suppose a random sample of 64 purchasers of this table saw is taken. The probability that the sample mean will be less than 82 minutes is __________. A. 0.6554

10. A manufacturer of power tools claims that the mean amount of time required to assemble their top-of-the-line table saw is 80 minutes with a standard deviation of 40 minutes. Suppose a random sample of 64 purchasers of this table saw is taken. The probability that the sample mean will be between 77 and 89 minutes is __________. A. 0.6898

11. A manufacturer of power tools claims that the mean amount of time required to assemble their top-of-the-line table saw is 80 minutes with a standard deviation of 40 minutes. Suppose a random sample of 64 purchasers of this table saw is taken. The probability that the sample mean will be greater than 88 minutes is __________. A. 0.0548

12. A manufacturer of power tools claims that the mean amount of time required to assemble their top-of-the-line table saw is 80 minutes with a standard deviation of 40 minutes. Suppose a random sample of 64 purchasers of this table saw is taken. So, the middle 95% of the sample means based on samples of size 64 will be between __________ and __________. A. 70.2 and 89.8 minutes

13. A numerical measure from a population, such as a population mean, is called _____. A. a parameter

14. A numerical measure from a population, such as a population mean, is called _____. A. a parameter

15. A numerical measure from a population, such as a population mean, is called _____. A. a parameter

16. A numerical measure from a population, such as a population mean, is called A. a parameter

17. A numerical measure from a sample, such as a sample mean, is known as _____. A. a statistic

18. A numerical measure from a sample, such as a sample mean, is known as _____. A. a statistic

19. A numerical measure from a sample, such as a sample mean, is known as _____. A. a statistic

20. A numerical measure from a sample, such as a sample mean, is known as A. a statistic

21. A parameter is a characteristic of a sample. True or False A. false

22. A population consists of 500 elements. We want to draw a simple random sample of 50 elements from this population. On the first selection, the probability of an element being selected is _____. A. 002

23. A population consists of 500 elements. We want to draw a simple random sample of 50 elements from this population. On the first selection, the probability of an element being selected is _____. A. .002

24. A population consists of 8 items. The number of different simple random samples of size 3 (without replacement) that can be selected from this population is _____. A. 56

25. A population consists of 8 items. The number of different simple random samples of size 3 (without replacement) that can be selected from this population is _____. A. 56

26. A population consists of 8 items. The number of different simple random samples of size 3 (without replacement) that can be selected from this population is _____. A. 56

27. A population consists of 8 items. The number of different simple random samples of size 3 (without replacement) that can be selected from this population is _____. A. 56

28. A population has a mean of 180 and a standard deviation of 24. A sample of 64 observations will be taken. The probability that the mean from that sample will be between 183 and 186 is _____. A. 0.1359

29. A population has a mean of 180 and a standard deviation of 24. A sample of 64 observations will be taken. The probability that the mean from that sample will be between 183 and 186 is _____. A. 0.1359

30. A population has a mean of 180 and a standard deviation of 24. A sample of 64 observations will be taken. The probability that the mean from that sample will be between 183 and 186 is A. 0.1359

31. A population has a mean of 180 and a standard deviation of 24. A sample of 64 observations will be taken. The probability that the mean from that sample will be between 183 and 186 is _____. A. 0.1359.

32. A population has a mean of 180 and a standard deviation of 24. A sample of 64 observations will be taken. The probability that the mean from that sample will be between 183 and 186 is _____. A. 0.1359

34. A population has a mean of 53 and a standard deviation of 21. A sample of 49 observations will be taken. The probability that the sample mean will be greater than 57.95 A. .0495

35. A population has a mean of 53 and a standard deviation of 21. A sample of 49 observations will be taken. The probability that the sample mean will be greater than 57.95 is _____. A. .0495

36. A population has a mean of 53 and a standard deviation of 21. A sample of 49 observations will be taken. The probability that the sample mean will be greater than 57.95 is _____. A. .0495

37. A population has a mean of 80 and a standard deviation of 7. A sample of 49 observations will be taken. The probability that the mean from that sample will be larger than 82 is _____. A. 0228

38. A population has a mean of 80 and a standard deviation of 7. A sample of 49 observations will be taken. The probability that the mean from that sample will be larger than 82 is _____. A. .0228

39. A population has a mean of 80 and a standard deviation of 7. A sample of 49 observations will be taken. The probability that the mean from that sample will be larger than 82 is _____. A. 0228

40. A population has a mean of 84 and a standard deviation of 12. A sample of 36 observations will be taken. The probability that the sample mean will be between 80.54 and 88.9 is _____. A. .9511

41. A population has a mean of 84 and a standard deviation of 12. A sample of 36 observations will be taken. The probability that the sample mean will be between 80.54 and 88.9 is _____. A. .9511

42. A population has a mean of 84 and a standard deviation of 12. A sample of 36 observations will be taken. The probability that the sample mean will be between 80.54 and 88.9 is A. 0.9511

43. A population has a means of 180 and a sd of 24. a sample of 64 observations will be taken. the probability that the mean from the sample will be between 183 and 186 is A. .1359

44. A population has a means of 80 and a sd of 7. A sample of 49 observations will be taken. The probability that the mean from that sample will be larger than 82 is A. .0228

45. A population of size 1,000 has a proportion of .5. Therefore, the proportion and the standard deviation of the sample proportion for samples of size 100 are _____. A. .5 and .047

46. A population of size 1,000 has a proportion of .5. Therefore, the proportion and the standard deviation of the sample proportion for samples of size 100 are _____. A. .5 and .047

47. A population of size 1,000 has a proportion of .5. therefore, the proportion and the standard deviation of the sample proportion for sample of size 100 are A. .5 and .050

48. A population parameter varies from one sample to the next. True or False A. false

49. A probability distribution for all possible values of a sample statistic is known as a _____. A. sampling distribution

50. A probability distribution for all possible values of a sample statistic is known as a _____. A. sampling distribution

51. A probability distribution for all possible values of a sample statistic is known as a _____. A. sampling distribution

52. A probability distribution for all possible values of a sample statistic is known as a _____. A. sampling distribution

53. A probability sampling method in which we randomly select one of the first k elements and then select every kth element thereafter is _____. A. systematic sampling

54. A probability sampling method in which we randomly select one of the first k elements and then select every kth element thereafter is _____. A. systematic sampling

55. A probability sampling method in which we randomly select one of the first k elements and then select every kth element thereafter is _____. A. systematic sampling

56. A probability sampling method in which we randomly select one of the first k elements and then select every kth element thereafter is: A. systematic sampling.

57. A probability sampling method in which we randomly select one of the first k elements and then select every kth element thereafter is _____. A. systematic sampling

58. A random sample of 12 four-year-old red pine trees was selected and the diameter (in inches) of each tree’s main stem was measured. The resulting observations are as follows:
11.3, 10.7, 12.4, 15.2, 10.1, 12.1 , 16.2, 10.5, 11.4, 11.0, 10.7, and 12.0
Find the point estimate that can be used to estimate the true population mean A.. x̅ = 11.97

59. A random sample of 121 bottles of cologne showed an average content of 4 ounces. It is known that the standard deviation of the contents (i.e., of the population) is .22 ounces. In this problem, the value .22 ounces is: A. a parameter.

60. A random sample of 121 bottles of cologne showed an average content of 4 ounces. It is known that the standard deviation of the contents (i.e., of the population) is 0.22 ounces.
Refer to Exhibit 7-4. The standard error of the mean equals _____.  A. .0200

61. A random sample of 121 bottles of cologne showed an average content of 4 ounces. It is known that the standard deviation of the contents (i.e., of the population) is 0.22 ounces.
Refer to Exhibit 7-4. The point estimate of the mean content of all bottles is _____. A. 4

62. A random sample of 121 bottles of cologne showed an average content of 4 ounces. It is known that the standard deviation of the contents (i.e., of the population) is 0.22 ounces.
Refer to Exhibit 7-4. In this problem, the .22 is _____.  A. a parameter

63. A random sample of 150 people was taken from a very large population. Ninety of the people in the sample were females. The standard error of the proportion of females is _____. A. .0400

64. A random sample of 150 people was taken from a very large population. Ninety of the people in the sample were female. The standard error of the proportion is: A. .0400.

65. A random sample of 150 people was taken from a very large population. Ninety of the people in the sample were females. The standard error of the proportion of females is _____. A. .0400

67. A random sample of 150 people was taken from a very large population. Ninety of the people in the sample were females. The standard error of the proportion of females is _____ A. 0.0400

68. A random sample of 150 people was taken from a very large population. 90 of the people in the sample were females. The standard error of the proportion of females is A. .0400

69. A random sample of 150 people was taken from a very large population. Ninety of the people in the sample were females. The standard error of the proportion of females is _____. A. .0400

70. A sample of 24 observations is taken from a population that has 150 elements. The sampling distribution of x bar (x with line over it) is _____. A. normal if the population is normally distributed

71. A sample of 24 observations is taken from a population that has 150 elements. The sampling distribution of x bar (x with line over it) is _____. A. normal if the population is normally distributed

72.  A sample of 25 observations is taken from a process (an infinite population). The sampling distribution of is _____. A. approximately normal if np ≥ 5 and n(1 – p) ≥ 5

73. A sample of 25 observations is taken from a process (an infinite population). The sampling distribution of is _____. A. approximately normal if np ≥ 5 and n(1 – p) ≥ 5

74. A sample of 25 observations is taken from a process (an infinite population). The sampling distribution of is _____. A. approximately normal if np ≥ 5 and n(1 – p) ≥ 5

75. A sample of 25 observations is taken from a process. the sampling distribution of p is A. approx. normal if np> or equal to 5 and n(1-p)>or equal to 5

76. A sample of 400 observations will be taken from a process (an infinite population). The population proportion equals .8. The probability that the sample proportion will be greater than 0.83 is _____. A. .0668

77. A sample of 400 observations will be taken from a process (an infinite population). The population proportion equals .8. The probability that the sample proportion will be greater than 0.83 is _____. A. .0668

78. A sample of 400 observations will be taken from a process (an infinite population). The population proportion equals .8. The probability that the sample proportion will be greater than 0.83 is _____. A. .0668

79. A sample of 400 observations will be taken from a process. the population proportion equals .8. the probability that the sample proportion will be greater than .83 is A. .0668

80. A sample of 400 observations will be taken from an infinite population. The population proportion equals .8. The probability that the sample proportion will be greater than .83 is: A. .0668.

81. A sample of 51 observations will be taken from a process (an infinite population). The population proportion equals .85. The probability that the sample proportion will be between .9115 and .946 is _____. A. .0819

82. A sample of 51 observations will be taken from a process (an infinite population). The population proportion equals .85. The probability that the sample proportion will be between .9115 and .946 is _____. A. 0819

83. A sample of 51 observations will be taken from a process (an infinite population). The population proportion equal .85. The probability that the sample proportion will be between .9115 and .946 A. .0819

84. A sample of 66 observations will be taken from a process (an infinite population). The population proportion equals .12. The probability that the sample proportion will be less than .1768 is _____. A. .9222

85. A sample of 66 observations will be taken from a process (an infinite population). The population proportion equals .12. The probability that the sample proportion will be less than .1768 is _____. A. .9222

86. A sample of 66 observations will be taken from a process (an infinite population). The population proportion equals .12. The probability that the sample proportion will be less than .1768 is _____. A. 9222

87. A sample of 66 observations will be taken from an infinite population. The population proportion equals .12. The probability that the sample proportion will be less than .1768 is: A. .92.

88. A sample of 92 observations is taken from a process (an infinite population). The sampling distribution of is approximately normal because _____. A. of the central limit theorem

89. A sample of 92 observations is taken from a process (an infinite population). The sampling distribution of is approximately normal because _____. A. of the central limit theorem

90. A sample of 92 observations is taken from an infinite population. The sampling distribution of is approximately: A. normal because of the central limit theorem.

91. A sample of 92 observations is taken from an infinite population. The sampling distribution of X(bar) is approximately: A. normal because of the central limit theorem.

92. A sample statistic, such as (x-bar), that estimates the value of the corresponding population parameter is known as a _____. A. point estimator

93. A sample statistic, such as x bar (mean: x with line over) , that estimates the value of the corresponding population parameter is known as a _____. A. point estimator

94. A sample statistic, such as x bar (mean: x with line over) , that estimates the value of the corresponding population parameter is known as a _____. A. point estimator

95. A sample statistic, such as x̄, that estimates the value of the corresponding population parameter is known as a _____. A. point estimator

96. A sample statistic, such as x̄, that estimates the value of the corresponding population parameter is known as a _____. A. point estimator

97. A sample that does not provide a good representation of the population from which it was collected is referred to as a(n) sample. A. biased

98. A simple random sample from a process (an infinite population) is a sample selected such that _____. A. each element selected comes from the same population and each element is selected independently

99. A simple random sample from a process (an infinite population) is a sample selected such that _____. A. each element selected comes from the same population and each element is selected independently

100. A simple random sample from a process (an infinite population) is a sample selected such that _____. A. each element selected comes from the same population and each element is selected independently

101. A simple random sample of 100 observations was taken from a large population. The sample mean and the standard deviation were determined to be 80 and 12, respectively. The standard error of the mean is: A. 1.20.

102. A simple random sample of 28 observations was taken from a large population. The sample mean equaled 50. Fifty is a _____. A. point estimate

103. A simple random sample of 28 observations was taken from a large population. The sample mean equaled 50. Fifty is a _____. A. point estimate

104. A simple random sample of 28 observations was taken from a large population. The sample mean equaled 50. Fifty is a _____. A. point estimate

105. A simple random sample of 5 observations from a population containing 400 elements was taken, and the following values were obtained.
12 18 19 20 21
A point estimate of the population mean is _____. A. 18

106. A simple random sample of 5 observations from a population containing 400 elements was taken, and the following values were obtained.
12 18 19 20 21
A point estimate of the population mean is _____. A. 18

107. A simple random sample of 5 observations from a population containing 400 elements was taken, and the following values were obtained. A. 18

108. A simple random sample of 64 observations was taken from a large population. The population standard deviation is 120. The sample mean was determined to be 320. The standard error of the mean is _____. A. 15

109. A simple random sample of 64 observations was taken from a large population. The population standard deviation is 120. The sample mean was determined to be 320. The standard error of the mean is _____. A. 15

110. A simple random sample of 64 observations was taken from a large population. The sample mean and standard deviation were determined to be 320 and 120, respectively. The standard error of the mean is: A. 15.

111. A simple random sample of 64 observations was taken from a large population. The sample mean and standard deviation were determined to be 320 and 120, respectively. The standard error of the mean is:
40.
15.
1.875.
5. A. 15.

112. A simple random sample of 64 observations was taken from a large population. The population standard deviation is 120. The sample mean was determined to be 320. The standard error of the mean is A. 15

113. A simple random sample of size n from a finite population of size N is a sample selected such that each possible sample of size _____. A. n has the same probability of being selected

114. A simple random sample of size n from a finite population of size N is a sample selected such that each possible sample of size _____. A. n has the same probability of being selected

115. A simple random sample of size n from a finite population of size N is to be selected. Each possible sample should have _____. A. the same probability of being selected

116. A simple random sample of size n from a finite population of size N is a sample selected such that each possible sample of size: A. n has the same probability of being selected.

117. A simple random sample of size n from a finite population of size N is a sample selected such that each possible sample of size _____. A. n has the same probability of being selected

118. A simple random sample of size n from a finite population of size N is to be selected. Each possible sample should have _____. A. the same probability of being selected

119. A simple random sample of size n from an infinite population is a sample selected such that: A. each element is selected independently and is selected from the same population.

120. A simple random sample of size n from an infinite population of size N is to be selected. Each possible sample should have: A. the same probability of being selected.

121. A single numerical value used as an estimate of a population parameter is known as a_____. A. point estimate

122. A single numerical value used as an estimate of a population parameter is known as a_____. A. point estimate

123. A single numerical value used as an estimate of a population parameter is known as a_____. A. point estimate

124. A single numerical value used as an estimate of a population parameter is known as a_____. A. point estimate

125. A statistics teacher started class one day by drawing the names of 10 students out of a hat and asked them to do as many pushups as they could. The 10 randomly selected students averaged 15 pushups per person with a standard deviation of 9 pushups. Suppose the distribution of the population of number of pushups that can be done is approximately normal. Which of the following statements is true? A. A t distribution should be used because σ is unknown.

126. A study at a college in the west coast reveals that, historically, 45% of the students are minority students. The expected percentage of minority students in their next group of freshmen is _______. A. 45%

127. A study at a college in the west coast reveals that, historically, 45% of the students are minority students. If random samples of size 75 are selected, the standard error of the proportion of students in the samples who are minority students is _________. A. 0.05745

128. A study at a college in the west coast reveals that, historically, 45% of the students are minority students. If a random sample of size 75 is selected, the probability is _______ that between 30% and 50% of the students in the sample will be minority students. A. 0.8034 using Excel or 0.8033 using Table E.2

129. A study at a college in the west coast reveals that, historically, 45% of the students are minority students. If a random sample of size 75 is selected, the probability is _______ that more than half of the students in the sample will be minority students A. 0.1920 using Excel or 0.1922 using Table E.2

130. A study at a college in the west coast reveals that, historically, 45% of the students are minority students. If random samples of size 75 are selected, 80% of the samples will have less than ______% of minority students. A. 49.83

131. A study at a college in the west coast reveals that, historically, 45% of the students are minority students. If random samples of size 75 are selected, 95% of the samples will have more than ______% of minority students. A. 35.55

132. A subset of a population selected to represent the population is a _____. A. None of these answers are correct.

133. A subset of a population selected to represent the population is a _____. A. sample

134. A subset of a population selected to represent the population is a _____. A. sample

135. A subset of a population selected to represent the population is a _____. A. sample

136. A theorem that allows us to use the normal probability distribution to approximate the sampling distribution of sample means and sample proportions whenever the sample size is large is known as the _____. A. central limit theorem

137. A theorem that allows us to use the normal probability distribution to approximate the sampling distribution of sample means and sample proportions whenever the sample size is large is known as the _____. A. central limit theorem

138. A theorem that allows us to use the normal probability distribution to approximate the sampling distribution of sample means and sample proportions whenever the sample size is large is known as the _____. A. central limit theorem

139. A theorem that allows us to use the normal probability distribution to approximate the sampling distribution of sample means and sample proportions whenever the sample size is large is known as the _____. A. central limit theorem

140. According to a survey, only 15% of customers who visited the web site of a major retail store made a purchase. Random samples of size 50 are selected.
The mean of all the sample proportions of customers who will make a purchase after visiting the web site is _______.
The standard deviation of all the sample proportions of customers who will make a purchase after visiting the web site is ________.
The requirements for using a normal distribution to approximate a binomial distribution is fulfilled.
what proportion of the samples will have between 20% and 30% of customers who will make a purchase after visiting the web site?
What proportion of the samples will have less than 15% of customers who will make a purchase after visiting the web site?
What is the probability that a random sample of 50 will have at least 30% of customers who will make a purchase after visiting the web site?
90% of the samples will have less than what percentage of customers who will make a purchase after visiting the web site?
90% of the samples will have more than what percentage of customers who will make a purchase after visiting the web site? A. 0.15 or 15%
0.05050
True
0.1596
0.5
0.0015
21.47%
8.528% using Excel or 8.536% using Table E.2

141. According to an article, 19% of the entire population in a developing country have high-speed access to the Internet. Random samples of size 200 are selected from the country’s population.
The population mean of all the sample proportions is ______.
The standard error of all the sample proportions is ______.
Among all the random samples of size 200, ______ % will have between 14% and 24% who have high-speed access to the Internet.
Among all the random samples of size 200, ______ % will have between 9% and 29% who have high-speed access to the Internet.
Among all the random samples of size 200, ______ % will have more than 30% who have high-speed access to the Internet.
Among all the random samples of size 200, ______ % will have less than 20% who have high-speed access to the Internet.
Among all the random samples of size 200, 90 % will have less than _____% who have high-speed access to the Internet.
Among all the random samples of size 200, 90 % will have more than _____% who have high-speed access to the Internet. A. 19% or 0.19
0.0277
92.85 using Excel or 92.82 using Table E.2
99.97
0.0000 or virtually zero
64.08 using Excel or 64.06 using Table E.2
22.56 using Excel or 22.55 using Table E.2
15.45

142. All of the following are true about the standard error of the mean EXCEPT _____. A. it is larger than the standard deviation of the population

143. All of the following are true about the standard error of the mean EXCEPT _____. A. it is larger than the standard deviation of the population

144. All of the following are true about the standard error of the mean EXCEPT _____. A. it is larger than the standard deviation of the population

145. All of the following are true about the standard error of the mean EXCEPT _____. A. it is larger than the standard deviation of the population

146. An 80% confidence interval will be A.  narrower than a 95% confidence interval

147. An approximate value of a population parameter that provides limits and believed to contain the value of the parameter is known as the: A. interval estimate.

148. An increase in the population standard deviation ______________ the width of confidence intervals. A. ncreases

149. As a general rule, the sampling distribution of the sample proportions can be approximated by a normal probability distribution whenever _____. A. np ≥ 5 and n(1 − p) ≥ 5

150. As a general rule, the sampling distribution of the sample proportions can be approximated by a normal probability distribution whenever _____. A. np ≥ 5 and n(1 − p) ≥ 5

151. As a general rule, the sampling distribution of the sample proportions can be approximated by a normal probability distribution whenever A. Both np ³ 5 and n(1 – p) ³ 5 are true.

152. As a general rule, the sampling distribution of the sample proportions can be approximated by a normal probability distribution whenever _____. A. np ≥ 5 and n(1 − p) ≥ 5

153. As a rule of thumb, the sampling distribution of the sample proportion can be approximated by a normal probability distribution when: A. n(1 – p) ≥ 5 and np ≥ 5.

154. As the number of degrees of freedom for a t distribution increases, the difference between the t distribution and the standard normal distribution: A. becomes smaller.

155. As the sample size becomes larger, the sampling distribution of the sample mean approaches a _____. A. normal probability distribution

156. As the sample size becomes larger, the sampling distribution of the sample mean approaches a _____. A. normal probability distribution

157. As the sample size increases, the _____. A. standard error of the mean decreases

158. As the sample size increases, the _____. A. standard error of the mean decreases

159. As the sample size increases, the _____. A. standard error of the mean decreases

160. As the sample size increases, the _____. A. standard error of the mean decreases

161. As the sample size increases, the margin of error: A. decreases

162. As the sample size increases, the variability among the sample means _____. A. decreases

163. As the sample size increases, the variability among the sample means _____. A. decreases

164. As the sample size increases, the variability among the sample means _____. A. decreases

165. As the sample size increases, the variability among the sample means _____. A. decreases

166. As the sample size increases, the variability among the sample means _____. A. decreases

167. As the sample size increases, the: A. standard error of the mean decreases.

168. Assume that house prices in a neighborhood are normally distributed with a standard deviation of $20,000. A random sample of 16 observations is taken. What is the probability that the sample mean differs from the population mean by more than $5,000? A. 0.3173 using Excel or 0.3174 using Table E.2

169. Assuming income is normally distributed, what is the probability that? x – = 41,397 A. 0.0

170. At a computer manufacturing company, the actual size of a particular type of computer chips is normally distributed with a mean of 1 centimeter and a standard deviation of 0.1 centimeter. A random sample of 12 computer chips is taken. What is the standard error for the sample mean? A. 0.029

171. At a computer manufacturing company, the actual size of a particular type of computer chips is normally distributed with a mean of 1 centimeter and a standard deviation of 0.1 centimeter. A random sample of 12 computer chips is taken. What is the probability that the sample mean will be between 0.99 and 1.01 centimeters? A. 0.2710 using Excel or 0.2736 using Table E.2

172. At a computer manufacturing company, the actual size of a particular type of computer chips is normally distributed with a mean of 1 centimeter and a standard deviation of 0.1 centimeter. A random sample of 12 computer chips is taken. What is the probability that the sample mean will be below 0.95 centimeters? A. 0.0416 using Excel or 0.0418 using Table E.2

173. At a computer manufacturing company, the actual size of a particular type of computer chips is normally distributed with a mean of 1 centimeter and a standard deviation of 0.1 centimeter. A random sample of 12 computer chips is taken. Above what value do 2.5% of the sample means fall? A. 1.057

174. Cluster sampling is _____. A. a probability sampling method

175. Cluster sampling is _____. A. a probability sampling method

176. Cluster sampling is _____. A. a probability sampling method

177. Cluster sampling is: A. a probability sampling method.

178. Consider a population of 5 families with the following data representing the number of pets in each family.
Family
Number of Pets
A
2
B
6
C
4
D
3
E
1 A. a) AB 4, AC 3, AD 2.5, AE 1.5, BC 5, BD 4.5, BE 3.5, CD, 3.5, CE 2.5, DE 2
b) 3.2, 2.956
c) 3.2, 0.43

179. Consider a population with a mean of 20 and a standard deviation of 3. You take a sample of size 36. What is the expected value of the sample mean? A. 20

180. Consider a population with a mean of 20 and a standard deviation of 3. You take a sample of size 36. What is the standard error of the mean? A. 1/2

181. Convenience sampling is a: A. nonprobability sampling technique.

182. Convenience sampling is an example of _____. A. a nonprobability sampling technique

183. Convenience sampling is an example of _____. A. a nonprobability sampling technique

184. Convenience sampling is an example of _____. A. a nonprobability sampling technique.

185. Convenience sampling is an example of _____. A. nonprobability sampling technique

186. Doubling the size of the sample will _____. A. reduce the standard error of the mean to approximately 70% of its current value

187. Doubling the size of the sample will _____. A. reduce the standard error of the mean to approximately 70% of its current value

188. Doubling the size of the sample will: A. reduce the standard error of the mean.

189. Excel’s RAND function _____. A. generates random numbers

190. Excel’s RAND function _____. A. generates random numbers

191. Excel’s RAND function _____. A. returns a random decimal number between 0 and 1.
Exhibit 7-2
Four hundred registered voters were randomly selected and asked whether gun laws should be changed. Three hundred said “yes,” and 100 said “no.”
Refer to Exhibit 7-2. The point estimate of the proportion in the population who will respond “yes” is _____. A. .75

192. Exhibit 7-2
Four hundred registered voters were randomly selected and asked whether gun laws should be changed. Three hundred said “yes,” and 100 said “no.”
Refer to Exhibit 7-2. The point estimate of the proportion in the population who will respond “no” is _____. A. 25

193. Exhibit 7-4
A random sample of 121 bottles of cologne showed an average content of 4 ounces. It is known that the standard deviation of the contents (i.e., of the population) is 0.22 ounces.
Refer to Exhibit 7-4. The standard error of the mean equals _____. A. .0200

194. Exhibit 7-4
A random sample of 121 bottles of cologne showed an average content of 4 ounces. It is known that the standard deviation of the contents (i.e., of the population) is 0.22 ounces.
Refer to Exhibit 7-4. The point estimate of the mean content of all bottles is _____. A. a parameter

195. Exhibit 7-4
A random sample of 121 bottles of cologne showed an average content of 4 ounces. It is known that the standard deviation of the contents (i.e., of the population) is 0.22 ounces.
Refer to Exhibit 7-4. The point estimate of the mean content of all bottles is _____. A. 4

196. Exhibit 7-5
Random samples of size 17 are taken from a population that has 200 elements, a mean of 36, and a standard deviation of 8.
Refer to Exhibit 7-5. The mean and the standard deviation of the sampling distribution of the sample means are _____.  A. 36 and 1.86

197. Exhibit 7-5
Random samples of size 17 are taken from a population that has 200 elements, a mean of 36, and a standard deviation of 8.
Refer to Exhibit 7-5. Which of the following best describes the form of the sampling distribution of the sample mean for this situation?  A. None of the answers is correct.
-Approximately normal because the sample size is small relative to the population size
-Approximately normal because of the central limit theorem
-exactly normal

198. For a fixed confidence level and population standard deviation, if we would like to cut our margin of error to 1/3 of the original size, we should take a sample size that is: A. nine times as large as the original sample size.

199. For a fixed confidence level and population standard deviation, if we would like to cut our margin of error in half, we should take a sample size that is: A. four times as large as the original sample size.
twice as large as the original sample size.

200. For a fixed sample size, n, in order to have a higher degree of confidence, the margin of error and the width of the interval: A. must be larger.

201.  For a population with an unknown distribution, the form of the sampling distribution of the sample mean is _____. A. approximately normal for large sample sizes

202. For a population with an unknown distribution, the form of the sampling distribution of the sample mean is _____. A. approximately normal for large sample sizes

203. For a population with an unknown distribution, the form of the sampling distribution of the sample mean is A. approximately normal for large sample sizes

204. For a population with an unknown distribution, the form of the sampling distribution of the sample mean is _____. A. approximately normal for large sample sizes

205. For a(n) _____ , it is impossible to construct a sampling frame. A. infinite population

206. For air travelers, one of the biggest complaints is of the waiting time between when the airplane taxis away from the terminal until the flight takes off. This waiting time is known to have a right skewed distribution with a mean of 10 minutes and a standard deviation of 8 minutes. Suppose 100 flights have been randomly sampled. Describe the sampling distribution of the mean waiting time between when the airplane taxis away from the terminal until the flight takes off for these
100 flights. A. Distribution is approximately normal with mean = 10 minutes and standard error = 0.8 minutes.

207. For sample size 1, the sampling distribution of the mean will be normally distributed A. only if the population is normally distributed

208. For sample size 16, the sampling distribution of the mean will be approximately normally distributed A. if the shape of the population is symmetrical.

209. For sample sizes greater than 30, the sampling distribution of the mean will be approximately normally distributed A. regardless of the shape of the population.

210. For the interval estimation of μ when σ is known and the sample is large, the proper distribution to use is: A. the normal distribution.

211. Four hundred registered voters were randomly selected and asked whether gun laws should be changed. Three hundred said “yes,” and 100 said “no.”
Refer to Exhibit 7-2. The point estimate of the proportion in the population who will respond “yes” is _____. A. .75

212. Four hundred registered voters were randomly selected and asked whether gun laws should be changed. Three hundred said “yes,” and 100 said “no.”
Refer to Exhibit 7-2. The point estimate of the proportion in the population who will respond “no” is _____.  A. .25

213. Four hundred registered voters were randomly selected asked whether gun laws should be changed. Three hundred said “yes,” and one hundred said “no.”
Refer to Exhibit 7-2. The point estimate of the proportion in the population who will respond “yes” is A. 0.75

214. From a population of 200 elements, the standard deviation is known to be 14. A sample of 49 elements is selected. It is determined that the sample mean is 56. The standard error of the mean is _____. A. less than 2

215. From a population of 200 elements, the standard deviation is known to be 14. A sample of 49 elements is selected. It is determined that the sample mean is 56. The standard error of the mean is _____. A. less than 2

216. From a population of 200 elements, the standard deviation is known to be 14. A sample of 49 elements is selected. It is determined that the sample mean is 56. The standard error of the mean is _____. A. less than 2

217. From a population of 500 elements, a sample of 225 elements is selected. It is known that the variance of the population is 900. The standard error of the mean is approximately _____. A. 1.4847

218. From a population of 500 elements, a sample of 225 elements is selected. It is known that the variance of the population is 900. The standard error of the mean is approximately _____. A. 1.4847

219. From a population of 500 elements, a sample of 225 elements is selected. It is known that the variance of the population is 900. The standard error of the mean is approximately A. 1.4847

220. From a population that is normally distributed, a sample of 30 elements is selected and the standard deviation of the sample is computed. For the interval estimation of μ, the proper distribution to use is the: A. t distribution with 29 degrees of freedom.

221. he set of all elements of interest in a study is _____. A. a population

222. How many different samples of size 3 (without replacement) can be taken from a finite population of size 10? A. 120

223. How many different samples of size 3 (without replacement) can be taken from a finite population of size 10? A. 120

224. How many different samples of size 3 (without replacement) can be taken from a finite population of size 10? A. 120

225. How many simple random samples of size 5 can be selected from a population of size 8? A. 56

226. If the expected value of a sample statistic is equal to the parameter it is estimating, then we call that sample statistic A. unbiased.

227. If the middle area is 0.90, what are the relevant z-scores? A. 1.645

228. If we are calculating a 99% confidence interval, how much area (probability) is in the upper tail? A. 0.005

229. If we consider the simple random sampling process as an experiment, the sample mean is _____. A. a random variable

230. If we consider the simple random sampling process as an experiment, the sample mean is _____. A. a random variable

231. If we consider the simple random sampling process as an experiment, the sample mean is _____. A. a random variable

232. If we don’t know the population standard deviation, when can we use a normal distribution instead of a t-distribution? A. when n is greater than or equal to 30

234. If we had 1,000 samples and were constructing a 90 percent confidence interval, how many confidence intervals would we expect to include the population mean? A. 900

235. If you are constructing a 90 percent confidence interval, what is the level of significance? A. 0.10

236. In a local university, 10% of the students live in the dormitories. A random sample of 100 students is selected for a study.
a.What is the probability that the sample proportion of students living in the dormitories is between .172 and .178? b.What is the probability that the sample proportion of students living in the dormitories is greater than .025? A. a) 0.00354
b) 0.9938

237. In a random sample of 16 observations, the variance of the sample mean is 4 times ____ than the population variance. A. smaller

238. In a recent Gallup Poll, the decision was made to increase the size of its random sample of voters from 1500 people to about 4000 people. The purpose of this increase is to: A. reduce the standard error of the estimate.

239. In a simple random sample, all observations in the population are equally likely to end up in the sample. True or false A. true

240. In a survey of public opinion concerning state aid to a particular city, every 40th person registered as a voter was interviewed, beginning with a person selected at random from among the first 40 listed. This is an example of: A. systematic sampling.

241. In an interval estimation for a proportion of a population, the critical value of z at 99% confidence is: A. 2.576

242. In computing the standard error of the mean, the finite population correction factor is NOT used when _____. A. n/N ≤ 0.05

243. In computing the standard error of the mean, the finite population correction factor is NOT used when _____. A. n/N ≤ 0.05

244. In computing the standard error of the mean, the finite population correction factor is used when: A. n/N>.05

245. In computing the standard error of the mean, the finite population correction factor is NOT used when _____. A. n/N ≤ 0.05

246. In general, higher confidence levels provide larger confidence intervals. One way to have high confidence and a small margin of error is to: A. increase the sample size.

247. In interval estimation, as the sample size becomes larger, the interval estimate: A. becomes narrower.

248. In point estimation, data from the _____. A. sample are used to estimate the population parameter

249. In point estimation, data from the _____. A. sample are used to estimate the population parameter

250. In point estimation, data from the _____. A. sample are used to estimate the population parameter

251. In stratified random sampling: A. randomly selected elements within each of the strata form the sample.

252. In stratified sampling, an observation can belong to multiple strata. True or false A. false

253. In this problem, the .22 is _____.
Refer to Exhibit 7-4 A. a parameter

254. increasing the sample size when calculating a confidence interval while keeping the confidence level constant will ____. A. reduce the margin of error resulting in a narrower confidence interval

255. It is impossible to construct a frame for a(n) _____. A. infinite population

256. It is impossible to construct a frame for a(n) _____. A. infinite population

257. Major league baseball salaries averaged $3.26 million with a standard deviation of $1.2 million in a certain year in the past. Suppose a sample of 100 major league players was taken. Find the approximate probability that the mean salary of the 100 players exceeded $3.5 million. A. 0.0228

258. Major league baseball salaries averaged $3.26 million with a standard deviation of $1.2 million in a certain year in the past. Suppose a sample of 100 major league players was taken. Find the approximate probability that the mean salary of the 100 players exceeded $4.0 million. A. Approximately 0

259. Major league baseball salaries averaged $3.26 million with a standard deviation of $1.2 million in a certain year in the past. Suppose a sample of 100 major league players was taken. Find the approximate probability that the mean salary of the 100 players was no more than $3.0 million. A. 0.0151

260. Major league baseball salaries averaged $3.26 million with a standard deviation of $1.2 million in a certain year in the past. Suppose a sample of 100 major league players was taken. Find the approximate probability that the mean salary of the 100 players was less than $2.5 million. A. Approximately 0

261. numerical characteristics of a population A. Parameters are:

262. Online customer service is a key element to successful online retailing. According to a marketing survey, 37.5% of online customers take advantage of the online customer service. Random samples of 200 customers are selected.
The population mean of all possible sample proportions is ______.
The standard error of all possible sample proportions is ______.
____ % of the samples are likely to have between 35% and 40% who take advantage of online customer service.
____ % of the samples are likely to have less than 37.5% who take advantage of online customer service.
90% of the samples proportions symmetrically around the population proportion will have between _____% and _____% of the customers who take advantage of online customer service.
95% of the samples proportions symmetrically around the population Proportion will have between _____% and _____% of the customers who take advantage of online customer service.  A. 0.375 or 37.5%
0.0342
53.48 using Excel or 53.46 using Table E.2
50
31.87 and 43.13
30.79 and 44.21

263. Random sample of size 17 are taken from a population that has 200 elements, a mean of 36, and a standard deviation of 8.
The means and the standard deviation of the sampling distribution of the sample mean are  A. 36 and 1.86

264. Random samples of size 100 are taken from a process (an infinite population) whose population proportion is .2. The mean and standard deviation of the distribution of sample proportions are _____. A. 2 and .04

265. Random samples of size 100 are taken from a process (an infinite population) whose population proportion is .2. The mean and standard deviation of the distribution of sample proportions are _____. A. .2 and .04

266. Random samples of size 100 are taken from a process (an infinite population) whose population proportion is .2. The mean and standard deviation of the distribution of sample proportions are _____. A. .2 and .04

267. Random samples of size 100 are taken from an infinite population whose population proportion is .2. The mean and standard deviation of the sample proportion are: A. 2 and .04.

268. Random samples of size 17 are taken from a population that has 200 elements, a mean of 36, and a standard deviation of 8.
Refer to Exhibit 7-5. The mean and the standard deviation of the sampling distribution of the sample means are _____. A. 36 and 1.86

269. Random samples of size 17 are taken from a population that has 200 elements, a mean of 36, and a standard deviation of 8.
Refer to Exhibit 7-5. Which of the following best describes the form of the sampling distribution of the sample mean for this situation? A. None of the answers is correct.
-Approximately normal because the sample size is small relative to the population size
-Approximately normal because of the central limit theorem
-exactly normal

270. Random samples of size 36 are taken from a process (an infinite population) whose mean and standard deviation are 20 and 15, respectively. The distribution of the population is unknown. The mean and the standard error of the distribution of sample mean are _____. A. 20 and 2.5

271. Random samples of size 36 are taken from a process (an infinite population) whose mean and standard deviation are 20 and 15, respectively. The distribution of the population is unknown. The mean and the standard error of the distribution of sample mean are _____. A. 20 and 2.5

272.  Random samples of size 49 are taken from a population that has 200 elements, a mean of 180, and a variance of 196. The distribution of the population is unknown. The mean and the standard error of the distribution of sample means are _____. A. 180 and 1.74

273. Random samples of size 49 are taken from a population that has 200 elements, a mean of 180, and a variance of 196. The distribution of the population is unknown. The mean and the standard error of the distribution of sample means are _____. A. 180 and 1.74

274. Random samples of size 525 are taken from a process (an infinite population) whose population proportion is .3. The standard deviation of the sample proportions (i.e., the standard error of the proportion) is _____. A. .0200

275. Random samples of size 525 are taken from a process (an infinite population) whose population proportion is .3. The standard deviation of the sample proportions (i.e., the standard error of the proportion) is _____. A. 0200

276. Random samples of size 525 are taken from a process (an infinite population) whose population proportion is .3. The standard deviation of the sample proportions (i.e., the standard error of the proportion) is _____. A. .0200

277. Random samples of size 525 are taken from an infinite population whose population proportion is .3. The standard deviation of the sample proportions (i.e., the standard error of the proportion) is _____. A. 0200

278. Random samples of size 81 are taken from a process (an infinite population) whose mean and standard deviation are 200 and 18, respectively. The distribution of the population is unknown. The mean and the standard error of the distribution of sample means are _____. A. 200 and 2

279. Random samples of size 81 are taken from a process (an infinite population) whose mean and standard deviation are 200 and 18, respectively. The distribution of the population is unknown. The mean and the standard error of the distribution of sample means are _____. A. 200 and 2

280. Random samples of size 81 are taken from a process (an infinite population) whose mean and standard deviation are 200 and 18, respectively. The distribution of the population is unknown. The mean and the standard error of the distribution of sample means are _____. A. 200 and 2

281. Random samples of size 81 are taken from a process (an infinite population) whose mean and standard deviation are 200 and 18, respectively. The distribution of the population is unknown. The mean and the standard error of the distribution of sample means are A. 200 and 2

282. Random samples of size 81 are taken from a process (an infinite population) whose mean and standard deviation are 200 and 18, respectively. The distribution of the population is unknown. The mean and the standard error of the distribution of sample means are _____. A. 200 and 2

283. Random sampling with and without replacement are very similar when the sample size is
____ relative to the population size. A. small

284. Sales prices of baseball cards from the 1960s are known to possess a right skewed distribution with a mean sale price of $5.25 and a standard deviation of $2.80. Suppose a random sample of 100 cards from the 1960s is selected. Describe the sampling distribution for the sample mean sale price of the selected cards. A. Normal with a mean of $5.25 and a standard error of $0.28

285. Sample statistics, such as x̅ , s, or p̅, that provide the point estimate of the population parameter are known as: A. point estimators.

286. Sampling bias occurs when the sample is _______ of the population. A. not representative

287. Sampling distributions describe the distribution of A. statistics

288. Sampling error occurs when the procedure used to select the random sample is not correct. A. false

289. Since the sample size is always smaller than the size of the population, the sample mean must A. None of the alternative ANSWERS is correct

290. Stratified random sampling is a method of selecting a sample in which _____. A. the population is first divided into groups, and then random samples are drawn from each group

291. Stratified random sampling is a method of selecting a sample in which _____. A. the population is first divided into groups, and then random samples are drawn from each group

292. Stratified random sampling is a method of selecting a sample in which _____. A. the population is first divided into groups, and then random samples are drawn from each group

293. Suppose a sample of n = 50 items is selected from a population of manufactured products and the weight, X, of each item is recorded. Prior experience has shown that the weight has a probability distribution with µ = 6 ounces and σ = 2.5 ounces. Which of the following is true about the sampling distribution of the sample mean if a sample of size 15 is selected? A. The mean of the sampling distribution is 6 ounces.

294. Suppose that Apple is conducting a survey of potential iPad users. Management believes that a person’s gender could affect a respondent’s answers. What type of sampling would ensure that the sample was composed of an equal number of male and female respondents? A. stratified

295. Suppose that for the population of UNCG students, the mean of GPA is 3.46 and the median of GPA is 3.02. If you randomly select a student from the population, the expected value of his or her GPA is _____. A. equal to 3.46

296. Suppose that n=10 and we are constructing an 80% confidence interval. What t score do we use? A. 1.383

297. Suppose that n=20 and we are constructing an 95% confidence interval. What t score do we use? A. 2.093

298. Suppose that p ¯ = .19 and n = 1000. What is the 95% confidence interval for the population A. (0.166, 0.214)

299. Suppose that p ¯ = 0.5 and n=25. What is s_{p} A.  0.10

300. Suppose the ages of students in Statistics 101 follow a right skewed distribution with a mean of 23 years and a standard deviation of 3 years. If we randomly sampled 100 students, which of the following statements about the sampling distribution of the sample mean age is incorrect? A. The standard deviation of the sampling distribution is equal to 3 years.

301. Suppose the population mean is 70 and the standard error of the mean is 5. What is the range of sample means within 10 of the population mean? A. (60,80)

302. Suppose the population mean is 70 and the standard error of the mean is 5. What is the z-score associated with a sample mean of 80? A. 2

303. Suppose the population proportion is 0.5 and the standard error of the proportion is 0.1. What is the z-score associated with a sample proportion of 0.47? A. -0.3

304. Suppose the population proportion is 0.84, and you want to know the probability of obtaining a sample proportion within 0.04 of the population proportion. What range are you considering? A. (0.80,0.88)

305. Suppose you have a population of 3 children with heights of 36, 50, and 52 inches. You select a random sample of 2 children. The expected value of x ¯ (x bar) is ____ A. 46 inches

306. Suppose you have two samples. Sample A was collected using probability and sample B was collected without using probability. Then sample A is representative and sample B is not. True or false A. false

307. Suppose you sample 2 observations out of a population of 5. If you sample with replacement, the total number of possible samples is ___. A. 25

308. Suppose you take a random sample of size 25 from a population where the population proportion is 0.5. What is the expected value of the sample proportion? A. 0.5

309. Suppose you take a random sample of size 25 from a population where the population proportion is 0.5. What is the standard error of the proportion? A. 0.1

310. Suppose you take a random sample of size 25 from a population where the population proportion is 0.5. Can we approximate the sampling distribution of p ¯ with the normal distribution? A. yes

311. Suppose you want to figure out the average number of credit hours among UNCG students. A sample of sophomores is a representative sample for your analysis. True or false A. false

312. The amount of bleach a machine pours into bottles has a mean of 36 oz. with a standard deviation of 0.15 oz. Suppose we take a random sample of 36 bottles filled by this machine. The probability that the mean of the sample exceeds 36.01 oz. is __________. A. 0.3446

313. The amount of bleach a machine pours into bottles has a mean of 36 oz. with a standard deviation of 0.15 oz. Suppose we take a random sample of 36 bottles filled by this machine. The probability that the mean of the sample is less than 36.03 is __________. A. 0.8849

314. The amount of bleach a machine pours into bottles has a mean of 36 oz. with a standard deviation of 0.15 oz. Suppose we take a random sample of 36 bottles filled by this machine. The probability that the mean of the sample is between 35.94 and 36.06 oz. is __________. A. 0.9836

315. The amount of bleach a machine pours into bottles has a mean of 36 oz. with a standard deviation of 0.15 oz. Suppose we take a random sample of 36 bottles filled by this machine. The probability that the mean of the sample is between 35.95 and 35.98 oz. is __________. A. 0.1891

316. The amount of bleach a machine pours into bottles has a mean of 36 oz. with a standard deviation of 0.15 oz. Suppose we take a random sample of 36 bottles filled by this machine. So, the middle 95% of the sample means based on samples of size 36 will be between __________ and __________. A. 35.951 and 36.049 ounces

317. The amount of tea leaves in a can from a particular production line is normally distributed with µ = 110 grams and σ = 25 grams. A sample of 25 cans is to be selected. What is the probability that the sample mean will be between 100 and 120 grams? A. 0.9545 using Excel or 0.9544 using Table E.2

318. The amount of tea leaves in a can from a particular production line is normally distributed with µ = 110 grams and σ = 25 grams. A sample of 25 cans is to be selected. What is the probability that the sample mean will be less than 100 grams? A. 0.0228

319. The amount of tea leaves in a can from a particular production line is normally distributed with µ = 110 grams and σ = 25 grams. A sample of 25 cans is to be selected. What is the probability that the sample mean will be greater than 100 grams? A. 0.9772

320. The amount of tea leaves in a can from a particular production line is normally distributed with µ = 110 grams and σ = 25 grams. A sample of 25 cans is to be selected. So, 95% of all sample means will be greater than how many grams? A. 101.7757

321. The amount of tea leaves in a can from a particular production line is normally distributed with µ = 110 grams and σ = 25 grams. A sample of 25 cans is to be selected. So, the middle 70% of all sample means will fall between what two values? A. 104.8 and 115.2

322. The amount of time required for an oil and filter change on an automobile is normally distributed with a mean of 45 minutes and a standard deviation of 10 minutes. A random sample of 16 cars is selected. What is the standard error of the mean? A. 2.5 minutes

323. The amount of time required for an oil and filter change on an automobile is normally distributed with a mean of 45 minutes and a standard deviation of 10 minutes. A random sample of 16 cars is selected. What is the probability that the sample mean is between 45 and 52 minutes? A. 0.4974

324. The amount of time required for an oil and filter change on an automobile is normally distributed with a mean of 45 minutes and a standard deviation of 10 minutes. A random sample of 16 cars is selected. What is the probability that the sample mean will be between 39 and 48 minutes? A. 0.8767

325. The amount of time required for an oil and filter change on an automobile is normally distributed with a mean of 45 minutes and a standard deviation of 10 minutes. A random sample of 16 cars is selected. 95% of all sample means will fall between what two values? A. 40.1 and 49.9 minutes

326. The amount of time required for an oil and filter change on an automobile is normally distributed with a mean of 45 minutes and a standard deviation of 10 minutes. A random sample of 16 cars is selected. 90% of the sample means will be greater than what value? A. 41.8 minutes

327. The average age of the MBA students in a statistics class is 30.7 years old. The ages of five randomly selected students from the class are: 36, 25, 25, 29, 30. What is the sampling error? A. -1.7 years

328. The average weekly earnings of bus drivers in a city are $950 (that is μ) with a standard deviation of $45 (that is σ). Assume that we select a random sample of 81 bus drivers.
a.Assume the number of bus drivers in the city is large compared to the sample size. Compute the standard error of the mean. b.What is the probability that the sample mean will be greater than $960?c.If the population of bus drivers consisted of 400 drivers, what would be the standard error of the mean? A. 5
0.0228
4.47

329. The basis for using a normal probability distribution to approximate the sampling distribution of x̄ A. the central limit theorem

330. The basis for using a normal probability distribution to approximate the sampling distribution of and is _____. A. the central limit theorem

331. The basis for using a normal probability distribution to approximate the sampling distribution of x̄ and p̄ is _____. A. the central limit theorem

332. The basis for using a normal probability distribution to approximate the sampling distribution of and is _____. A. the central limit theorem

333. The basis for using a normal probability distribution to approximate the sampling distribution of (x-bar) and (p-bar) is _____. A. the central limit theorem

334. The Central Limit Theorem is important in statistics because A. for a large n, it says the sampling distribution of the sample mean is approximately
normal, regardless of the shape of the population.

335. The central limit theorem is important in Statistics because it: A. enables reasonably accurate probabilities to be determined for events involving the sample average when the sample size is large regardless of the distribution of the variable.

336. The Central Limit Theorem plays an important role in statistics because it provides information about the shape of the ______. A.  sampling distribution when the sample size is sufficiently large

337. The Central Limit Theorem states that the sampling distribution of x ¯ is normally distributed as long as __________.  A. the sample size is large enough

338. The central limit theorem states that: A. if the sample size n is large, then the sampling distribution of the sample mean can be approximated by a normal distribution.

339. The difference between the value of the sample statistic and the value of the corresponding population parameter is called the _____. A. sampling error

340.  The difference between the value of the sample statistic and the value of the corresponding population parameter is called the _____. A. sampling error

341. The difference between the value of the sample statistic and the value of the corresponding population parameter is called the _____. A. sampling error

342. The distribution of the number of loaves of bread sold per week by a large bakery over the past 5 years has a mean of 7,750 and a standard deviation of 145 loaves. Suppose a random sample of n = 40 weeks has been selected. What is the approximate probability that the mean number of loaves sold in the sampled weeks exceeds 7,895 loaves? A. Approximately 0

343. The distribution of values taken by a statistic in all possible samples of the same size from the same population is the sampling distribution of: A. the sample.

344. The distribution of values taken by a statistic in all possible samples of the same size from the same population is called a: A. sampling distribution.

345. The expected value of equals the mean of the population from which the sample is drawn _____. A. for any sample size

346. The expected value of equals the mean of the population from which the sample is drawn _____. A. for any sample size

347. The expected value of the random variable is A. μ

348. The expected value of the random variable x bar (mean: x with line over it) is A. μ

349. The expected value of the random variable x bar (mean: x with line over it) is A. μ

350. The expected value of the random variable x̄ is A. μ

351. The expected value of x̄ equals the mean of the population from which the sample is drawn _____. A. for any sample size

352. The fact that the sampling distribution of sample means can be approximated by a normal probability distribution whenever the sample size becomes large is based on the: A. central limit theorem.

353. The fact that the sampling distribution of the sample mean can be approximated by a normal probability distribution whenever the sample size is large is based on the _____. A. central limit theorem

354. The fact that the sampling distribution of the sample mean can be approximated by a normal probability distribution whenever the sample size is large is based on the _____. A. central limit theorem

355. The fact that the sampling distribution of the sample mean can be approximated by a normal probability distribution whenever the sample size is large is based on the A. central limit theorem

356. The fact that the sampling distribution of the sample mean can be approximated by a normal probability distribution whenever the sample size is large is based on the _____. A. central limit theorem

357. The finite correction factor should be used in the computation of σx̄ and σȳ when n/N is greater than _____. A. 05

358. The finite correction factor should be used in the computation of when n/N is greater than _____. A. .05

359. The finite correction factor should be used in the computation of when n/N is greater than _____. A. .05

360. The following data was collected from a simple random sample from a process (an infinite population)
13,15,14,16,12
The point estimate of the population mean A. 14

361. The following data were collected from a simple random sample from a process (an infinite population). A. 1.581

362. The following data were collected from a simple random sample from a process (an infinite population). A. is 14

363. The following information was collected from a simple random sample of a population.
16 19 18 17 20 18
Refer to Exhibit 7-3. The point estimate of the mean of the population is A. 18.0

364. The lifetimes of a certain brand of light bulbs are known to be normally distributed with a mean of 1,600 hours and a standard deviation of 400 hours. A random sample of 64 of these light bulbs is taken.
What is the probability that the sample mean lifetime is more than 1,550 hours?
The probability is 0.15 that the sample mean lifetime is more than how many hours?
The probability is 0.20 that the sample mean lifetime differs from the population mean lifetime by at least how many hours? A. 0.8413
1,651.82 hours using Excel or 1,652 hours using Table E.2
64.08 hours using Excel or 64 hours using Table E.2

365. The margin of error in an interval estimate of the population mean is a function of all of the following except the: A. sample mean.

366. The mean and the standard deviation of the sampling distribution of the sample means are _____. A. 36 and 1.86

367. The mean of the population _____.
Refer to Exhibit 7-1. A. could be any value

368. The mean score of all pro golfers for a particular course has a mean of 70 and a standard deviation of 3.0. Suppose 36 pro golfers played the course today. Find the probability that the mean score of the 36 pro golfers exceeded 71. A. 0.0228

369. The mean selling price of new homes in a small town over a year was $115,000. The population standard deviation was $25,000. A random sample of 100 new home sales from this city was taken.
What is the probability that the sample mean selling price was more than $110,000?
What is the probability that the sample mean selling price was between $113,000 and $117,000?
What is the probability that the sample mean selling price was between $114,000 and $116,000?
Without doing the calculations, state in which of the following ranges the sample mean selling price is most likely to lie?  A. 0.9772
0.5763 using Excel or 0.5762 using Table E.2
0.3108
$114,000 — $116,000

370. The medical director of a company looks at the medical records of all 50 employees and finds that the mean systolic blood pressure for these employees is 126.07. The value of 126.07 is: A. a parameter.

371. The number of random samples (without replacement) of size 3 that can be drawn from a population of size 5 is _____. A. 10

372. The number of random samples (without replacement) of size 3 that can be drawn from a population of size 5 is _____. A. 10

373. The number of random samples (without replacement) of size 3 that can be drawn from a population of size 5 is _____. A. 10

374. The number of random samples (without replacement) of size 3 that can be drawn from a population of size 5 is _____. A. 10

375. The owner of a fish market has an assistant who has determined that the weights of catfish are normally distributed, with mean of 3.2 pounds and standard deviation of 0.8 pound. If a sample of 16 fish is taken, what would the standard error of the mean weight equal? A. 0.200

376. The owner of a fish market has an assistant who has determined that the weights of catfish are normally distributed, with mean of 3.2 pounds and standard deviation of 0.8 pound. If a sample of 25 fish yields a mean of 3.6 pounds, what is the Z-score for this observation? A. 2.500

377. The owner of a fish market has an assistant who has determined that the weights of catfish are normally distributed, with mean of 3.2 pounds and standard deviation of 0.8 pound. If a sample of 64 fish yields a mean of 3.4 pounds, what is probability of obtaining a sample mean this large or larger? A. 0.0228

378. The owner of a fish market has an assistant who has determined that the weights of catfish are normally distributed, with mean of 3.2 pounds and standard deviation of 0.8 pound. What percentage of samples of 4 fish will have sample means between 3.0 and 4.0 pounds? A. 67%

379. The point estimate of the mean content of all bottles is _____.
Refer to Exhibit 7-4 A. 4

380. The point estimate of the mean of the population is _____. A. 18.0

381. The point estimate of the population mean _____.
Refer to Exhibit 7-1 A. 14

382. The point estimate of the population standard deviation is _____.
Refer to Exhibit 7-3 A. 1.414

384. The point estimate of the population standard deviation is _____.
Refer to Exhibit 7-1 A. 1.581

385. The point estimate of the population standard deviation is A. 1.581

386. The point estimate of the proportion in the population who will respond “no” is _____.
Refer to Exhibit 7-2 A. .25

387. The point estimate of the proportion in the population who will respond “yes” is _____.
Refer to Exhibit 7-2 A. .75

388. The population being studied is usually considered ______ if it involves an ongoing process that makes listing or counting every element in the population impossible. A. infinite

389. The population distribution is the probability distribution of the population parameters. True or false A. false

390. The population proportion is 0.6. In a random sample from the population, you find a sample proportion of 0.64. The sampling error is _____. A. 0.04

391. The population we want to make inferences about is called the: A. target population.

392. The population we want to make inferences about is the _____. A. target population

393. The probability distribution of all possible values of the sample mean is called the ____. A. sampling distribution of the sample mean

394. The probability distribution of all possible values of the sample proportion is the _____. A. sampling distribution of

 395. The probability distribution of all possible values of the sample mean is called the ____. A. sampling distribution of the sample mean

396. The probability distribution of all possible values of the sample proportion p bar: (p with line over it) is the _____. A. sampling distribution of p bar: (p with line over it)

397. The probability distribution of all possible values of the sample mean is called the ____. A. sampling distribution of the sample mean

398. The probability distribution of all possible values of the sample proportion p̄ is the _____. A. sampling distribution of p̄

399. The probability distribution of all possible values of the sample proportion is the: A. sampling distribution of p̅.

400. The probability distribution of all possible values of the sample proportion p bar: (p with line over it) is the _____. A. sampling distribution of p bar: (p with line over it)

401. The probability distribution of all possible values of the sample proportion is the _____. A. sampling distribution of

402. The probability that the interval estimation procedure will generate an interval that does not contain µ is known as the: A. level of significance

403. The purpose of statistical inference is to provide information about the _____. A. population based upon information contained in the sample

404. The purpose of statistical inference is to provide information about the _____. A. population based upon information contained in the sample

405. The sample mean is the point estimator of _____. A. μ

406. The sample median is a point estimate of the population median. True or False A. True

407. The sample statistic s is the point estimator of _____. A. σ

408. The sample variance is a random variable. True or False A. true

409. The sampling distribution is the probability distribution of the sample. True or false A. false

410. The sampling distribution of can be approximated by a normal distribution as long as: A. np>=5 and n(1-0p)>=5

411. The sampling distribution of is the: A. probability distribution of all possible values of the sample proportion.

412. The sampling distribution of p̅ is the: A. probability distribution of all possible values of the sample proportion.

413. The sampling distribution of the proportion approximately follows the normal distribution when the values np and n(1-p) are greater than or equal to _____. A. 5

414. The sampling distribution of the sample mean _____. A. is the probability distribution showing all possible values of the sample mean

415. The sampling distribution of the sample mean A. is the probability distribution showing all possible values of the sample mean

416. The set of all elements of interest in a study is _____. A. a population

417. The set of all elements of interest in a study is _____. A. population

418. The standard deviation of a point estimator is called the: A. standard error.

419. The standard deviation of all possible mc006-1.jpg values is called the A. standard error of the mean

420. The standard deviation of all possible x bar (mean: x with line over it) values is called the _____. A. standard error of the mean

421. The standard deviation of all possible x bar (mean: x with line over it) values is called the _____. A. standard error of the mean

422. The standard deviation of all possible x̄ values is called the _____. A. standard error of the mean

423. The standard deviation of all possible x̄ values is called the _____. A. standard error of the mean

424. The standard deviation of all possible x values is called the A. standard error of the mean

425. The standard deviation of is referred to as the _____. A. standard error of the proportion

426. The standard deviation of is referred to as the _____. A. standard error of the mean

427. The standard deviation of is referred to as the _____. A. standard error of the proportion

428. The standard deviation of is referred to as the _____. A. standard error of the mean

429. The standard deviation of p is referred to as the A. standard error of the proportion

430. The standard deviation of x̄ is referred to as the _____. A. standard error of the mean

431. The standard deviation of x̄ is referred to as the _____. A. standard error of the mean

432. The standard error of the mean A. All of the above

434. The standard error of the mean equals _____.
Refer to Exhibit 7-4 A. .0200

435. The standard error of the mean for a sample of 100 is 30. In order to cut the standard error of the mean to 15, we would A. increase the sample size to 400.

436. The standard error of the population proportion will become larger A. as population proportion approaches 0.50.

437. The standard error of the proportion will become larger as _____. A. p approaches .5

438. The standard error of the proportion will become larger as _____. A. p approaches .5

439. The time spent studying by students in the week before final exams follows a normal distribution with a standard deviation of 8 hours. A random sample of 4 students was taken in order to estimate the mean study time for the population of all students.
What is the probability that the sample mean exceeds the population mean by more than 2 hours?
What is the probability that the sample mean is more than 3 hours below the population mean?
What is the probability that the sample mean differs from the population mean by less than 2 hours?
What is the probability that the sample mean differs from the population mean by more than 3 hours? A. 0.3085
0.2266
0.3829 using Excel or 0.3830 using Table E.2
0.4533 using Excel or 0.4532 using Table E.2

440. The value added and subtracted from a point estimate in order to develop an interval estimate of the population parameter is known as the: A. margin of error.

441. The value of the _____ is used to estimate the value of the population parameter. A. sample statistic

442. The value of the ___________ is used to estimate the value of the population parameter. A. sample statistic

445. The value of the ___________ is used to estimate the value of the population parameter. A. sample statistic

446. The value of the ___________ is used to estimate the value of the population parameter. A. sample statistic

447. The value of the ___________ is used to estimate the value of the population parameter. A. sample statistic

448. The value of the ___________ is used to estimate the value of the population parameter. A. sample statistic

449. The z value for a 99% confidence interval estimation is: A. 2.58

450. There are 500 employees in a firm, and 45% are female. A sample of 60 employees is selected randomly.
a.Determine the standard error of the proportion.b.What is the probability that the sample proportion of females is between .40 and .55? A. a) 0.06422
b) 0.7188

451. There are 6 children in a family. The number of children defines a population. The number of simple random samples of size 2 (without replacement) that are possible equals _____. A. 15

452. There are 6 children in a family. The number of children defines a population. The number of simple random samples of size 2 (without replacement) that are possible is equal to: A. 15.

453. There are 6 children in a family. The number of children defines a population. The number of simple random samples of size 2 (without replacement) that are possible is equal to:
15.
12.
3.
16.
A simple random sample of size n from a finite population of size N is a sample selected such that each possible sample of size A. 15.

454. There are 6 children in a family. The number of children defines a population. The number of simple random samples of size 2 (without replacement) that are possible equals _____. A. 15

455. There are 6 children in a family. The number of children defines a population. The number of simple random samples of size 2 (without replacement) that are possible equals _____. A. 15

456. To compute the necessary sample size for an interval estimate of a population proportion, all of the following procedures are recommended when p is unknown except: A. using .95 as an estimate.

457. To compute the necessary sample size for an interval estimate of a population mean, all of the following procedures are recommended when σ is unknown except: A. using σ = 1.

458. To save money, you are forced to use a sample of 10 observations rather than 25. The confidence intervals for n = 10 will be A. wider than confidence intervals for n = 25

459. To use the normal distribution to approximate the binomial distribution, we need ______ and ______ to be at least 5. A. π n and n (1-π )

460. True or false? A sample size of 18 is considered large enough to apply the Central Limit Theorem. A. false

461. True or false? To calculate a z-score for a sample mean, you need to calculate the standard error of the mean. A. true

462. True or false? Unlike the sample mean, increasing the sample size does not help us get a sample proportion closer to the population proportion. A. false

463. True or false? We can usually approximate the sampling distribution of LaTeX: \bar{p} p ¯ with the normal distribution. A. true

464. Under random sampling, the probability distribution of the population mean is its sampling distribution. True or false A. false

465. Using an α = .04, a confidence interval for a population proportion is determined to be .65 to .75. If the level of significance is decreased, the interval for the population proportion: A. becomes wider

466. We can reduce the margin of error in an interval estimate of p by doing any of the following except: A. increasing the planning value p* to .5.

467. We wish to draw a sample of size 5 without replacement from a population of 50 households. Suppose the households were numbered 01 to 50. Using the following line from a random number table, the households selected would be:
1 1 3 6 2 3 5 6 9 2 9 6 2 3 7 9 0 8 4 2 4 6 8 4 3 6 2 7 1 9 6 4 0 4 A. 11, 36, 23, 56, and 92

468. What happens as the sample size increases? A. sample of error decreases

469. What is the expected value for the sampling distribution of the sample mean? A. Always equal to the population mean

470. What is the main benefit of a larger sample size? A. There is a higher probability that the sample mean falls within a specified distance from the population mean

471. What is the relationship between the expected value of the sample mean and the population mean? A. the expected value of xbar

472. What is the standard error of the mean? A. The standard deviation of the sampling distribution of x –

473. What is the symbol for the population mean? A. μ

474. When “s” is used to estimate “σ,” the margin of error is computed by using the: A. t distribution.

475. When a variable follows a continuous distribution, what is the probability of one specific value occurring? A. 0.00

476. When drawing a sample from a population, the goal is for the sample to: A. match the targeted population.

477. When sampling without replacement, the same observation cannot be selected into your sample multiple times. True or false A. true

478. When the expected value of the point estimator is equal to the population parameter it estimates it is said to be _____? A. unbiased

479. When the level of confidence decreases, the margin of error: A. becomes smaller.

480. When the population has a normal distribution, the sampling distribution of is normally distributed _____. A. for any sample size

481. When the population has a normal distribution, the sampling distribution of x bar: (x with line over it) is normally distributed _____. A. for any sample size

482. When the population has a normal distribution, the sampling distribution of x bar: (x with line over it) is normally distributed _____. A. for any sample size

483. When the population has a normal distribution, the sampling distribution of is normally distributed _____. A. for any sample size

484. When the population has a normal distribution, the sampling distribution of (x-bar) is normally distributed _____. A. for any sample size

485. Whenever the population has a normal probability distribution, the sampling distribution of is a normal probability distribution for _____. A. any sample size

486. Whenever the population has a normal probability distribution, the sampling distribution of x̄ is a normal probability distribution for _____. A. any sample size

487. Whenever the population has a normal probability distribution, the sampling distribution of is a normal probability distribution for _____. A. any sample size

488. Which of the following best describes the form of the sampling distribution of the sample mean for this situation? A. none of the answers are correct

489. Which of the following distributions would have the widest spread? A. mu=0, s=5

490. Which of the following is a nonprobability sampling technique? A. Judgment sampling

491. Which of the following is a point estimator? A. S

492. Which of the following is an example of a nonprobability sampling technique? A. judgment sampling

493. Which of the following is not a symbol for a parameter? A. s

494. Which of the following is true about the sampling distribution of the sample mean? A. The mean of the sampling distribution is always µ

495. Which of the following is true regarding the sampling distribution of the mean for a large sample size? A. It has a normal distribution with the same mean as the population but with a smaller standard deviation.

496. Which of the following is(are) point estimator(s)? A. S

497. Which of the following is(are) true? A. II and III

498. Which of the following sampling methods does NOT lead to probability samples? A. convenience sampling

499. Which of the following statements about the sampling distribution of the sample mean is incorrect? A. The standard deviation of the sampling distribution of the sample mean is equal to σ.

500. Which of the following statements is not true regarding the characteristics of the Student’s t-distribution? A. The shape of the Student’s t-distribution is narrower than the size of the normal distribution

501. Which of the following statements regarding the sampling distribution of sample means is incorrect? A. The standard deviation of the sampling distribution is the standard deviation of the population.

502. Which of these best describes a sampling distribution of a statistic? A. It is the distribution of all of the statistics calculated from all possible samples of the same sample size.

503. Why is the Central Limit Theorem so important to the study of sampling distributions? A. It allows us to disregard the shape of the population when n is large.

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