1. 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 _____.               20 and 2.5
2. The expected value of equals the mean of the population from which the sample is drawn _____.  For any sample size
3. The basis for using a normal probability distribution to approximate the sampling distribution of and is _____.   the central limit theorem
4. The standard deviation of is referred to as the ____   standard error of the proportion
5. The standard deviation of is referred to as the _  standard error of the mean
6. The value of the ___________ is used to estimate the value of the population parameter.  sample statistic
7. The population being studied is usually considered ______ if it involves an ongoing process that makes listing or counting every element in the population impossible.  Infinite
8. A probability sampling method in which we randomly select one of the first k elements and then select every kth element thereafter is _____.   systematic sampling
9. The standard deviation of a point estimator is the _____.   standard error
10. The finite correction factor should be used in the computation of when n/N is greater than _____.   .05
11. The set of all elements of interest in a study is _____.   a population
12. A subset of a population selected to represent the population is a   sample
13. The purpose of statistical inference is to provide information about the   population based upon information contained in the sample
14. 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 ___    n has the same probability of being selected
15. The number of random samples (without replacement) of size 3 that can be drawn from a population of size 5 is      10
16. 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 _____.    15
17. How many different samples of size 3 (without replacement) can be taken from a finite population of size 10?    120
18. 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 _____.   56
19. 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 _____.   .002
20. Excel’s RAND function _____.   generates random numbers
21. A simple random sample of size n from a finite population of size N is to be selected. Each possible sample should have _____.   the same probability of being slected
22. A simple random sample from a process (an infinite population) is a sample selected such that _____.    each element selected comes from the same population and each element is selected independently
23. A numerical measure from a population, such as a population mean, is called _____   a parameter
24. A numerical measure from a sample, such as a sample mean, is known as _____.  a statistic
25. A sample statistic, such as , that estimates the value of the corresponding population parameter is known as a _____.   point estimator
26. A single numerical value used as an estimate of a population parameter is known as a_____.  point estimate
27. In point estimation, data from the _____.   sample are used to estimate the population parameter
28. The sample mean is the point estimator of _____   μ
29. The sample statistic s is the point estimator of   σ
30. 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 _____.    18
31. A probability distribution for all possible values of a sample statistic is known as a _____.  sampling distribution
32. A simple random sample of 28 observations was taken from a large population. The sample mean equaled 50. Fifty is a _____.   point estimate
33. If we consider the simple random sampling process as an experiment, the sample mean is _____.   a random variable
34. The probability distribution of all possible values of the sample mean is called the ____.  sampling distribution of the sample mean
35. The sampling distribution of the sample mean _____.   is the probability distribution showing all possible values of the sample mean
36. The difference between the value of the sample statistic and the value of the corresponding population parameter is called the _____.   sampling error
37. The expected value of the random variable is    M
38. The standard deviation of all possible values is called the _____.    standard error of the mean
39. In computing the standard error of the mean, the finite population correction factor is NOT used when _____.   n/N ≤ 0.05
40. A finite population correction factor is needed in computing the standard deviation of the sampling distribution of sample means _____.   whenever the sample size is more than 5% of the population size
41. 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 _____.   less than 2
42. 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 _____.   1.4847
43. 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 _____.   15
44. As the sample size increases, the _____.   standard error of the mean decreases
45. As the sample size increases, the variability among the sample means _____.   Decreases
46. Doubling the size of the sample will _____.   reduce the standard error of the mean to approzimately 70% of its current value
47. 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 _____.   180 and 1.74
48. 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 _____.  200 and 2
49. 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 _____.   central limit theorem
50. 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 _____.  central limit theorem
51. As the sample size becomes larger, the sampling distribution of the sample mean approaches a _____.   normal probability distribution
52. Whenever the population has a normal probability distribution, the sampling distribution of is a normal probability distribution for _____.   any sample size
53. For a population with an unknown distribution, the form of the sampling distribution of the sample mean is _____.   approzimately normal for large sample sizes
54. A sample of 24 observations is taken from a population that has 150 elements. The sampling distribution of is _____.  normal if the population is normally distributed
55. A sample of 92 observations is taken from a process (an infinite population). The sampling distribution of is approximately normal because _____.   of the central limit theorem
56. 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 _____.   0.0228
57. 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 _____.  0.1359
58. 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 _____.  0.9511
59. 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 _____. 0.495
60. Refer to Exhibit 7-1. The point estimate of the population mean _____.  is 14
61. Refer to Exhibit 7-1. The point estimate of the population standard deviation is _____. 1.581
62. Refer to Exhibit 7-1. The mean of the population _____.   could be any value
63. Refer to Exhibit 7-2. The point estimate of the proportion in the population who will respond “yes” is _____.    0.75
64. Refer to Exhibit 7-2. The point estimate of the proportion in the population who will respond “no” is _____. 0.25
65. Refer to Exhibit 7-3. The point estimate of the mean of the population is _____.  18.0
66. Refer to Exhibit 7-3. The point estimate of the population standard deviation is _____.  1.414
67. Refer to Exhibit 7-4. The standard error of the mean equals _____. .0200
68. Refer to Exhibit 7-4. The point estimate of the mean content of all bottles is _____.4
69. Refer to Exhibit 7-4. In this problem, the .22 is _____.  a parameter
70. Refer to Exhibit 7-5. The mean and the standard deviation of the sampling distribution of the sample means are _____.  36 and 1.86
71. The probability distribution of all possible values of the sample proportion is the _____.  sampling distribution of
72. 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 _____.  0.0200
73. 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 _____.  0.0400
74. 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 _____.  0.5 and 0.047
75. 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 _____.    0.2 and 0.04
76. As a general rule, the sampling distribution of the sample proportions can be approximated by a normal probability distribution whenever _____.   np ≥ 5 and n(1 − p) ≥ 5
77. A sample of 25 observations is taken from a process (an infinite population). The sampling distribution of is _____.  approximately normal if np ≥ 5 and n(1 – p) ≥ 5
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 _____.   0.0668
79. 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 _____.   0.9222
80. 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 _____.   0.0819
81. Stratified random sampling is a method of selecting a sample in which _____.  the population is first divided into groups, and then random samples are drawn from each group
82. Cluster sampling is _____.   a probability sampling method
83. Convenience sampling is an example of _____.  a nonprobability sampling technique
84. Which of the following is an example of a nonprobability sampling technique?  judment sampling
85. Which of the following sampling methods does NOT lead to probability samples?  convenience sampling
86. The population we want to make inferences about is the _____.   target population
87. When the population has a normal distribution, the sampling distribution of is normally distributed _____.   for any sample size
88. It is impossible to construct a frame for a(n) _____.  infinite population
89. The standard error of the proportion will become larger as _____.   p approaches 0.5
90. All of the following are true about the standard error of the mean EXCEPT _____.  it is larger than the standard deviation of the population

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