1. A 95% confidence interval for a population mean is determined to be 100 to 120. If the confidence coefficient is reduced to 0.90, the interval for μ   becomes narrower: The t distribution should be used whenever: the sample standard deviation is used to estimate the population standard deviation
2. 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
3. A numerical measure from a population, such as a population mean, is called  a parameter
4. 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
5. A probability distribution for all possible values of a sample statistic is known as a  sampling distribution
6. 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
7. A random sample of 144 observations has a mean of 20, a median of 21, and a mode of 22. The population standard deviation is known to equal 4.8. The 95.44% confidence interval for the population mean is  19.2 to 20.8
8. 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
9. A sample of 400 observations will be taken from a process (an infinite population). The population proportion equals 0.8. The probability that the sample proportion will be greater than 0.83 is  0.0668
10. A sample of 51 observations will be taken from a process (an infinite population). The population proportion equals 0.85. The probability that the sample proportion will be between 0.9115 and 0.946 is  0.0819
11. A sample of 66 observations will be taken from a process (an infinite population). The population proportion equals 0.12. The probability that the sample proportion will be less than 0.1768 is   0.9222
12. A sample statistic, such as , that estimates the value of the corresponding population parameter is known as a   point estimator
13. 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
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. 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 selected
16. A subset of a population selected to represent the population is a   sample
17. 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
18. A Type I error is committed when   a true null hypothesis is rejected
19. An estimate of a population parameter that provides an interval believed to contain the value of the parameter is known as the  interval estimate
20. An example of statistical inference is   hypothesis testing
21. An interval estimate is used to estimate   a population parameter
22. As a general guideline, the research hypothesis should be stated as the   alternative hypothesis
23. As the degrees of freedom increase, the t distribution approaches the  normal distribution
24. As the sample size increases, the  standard error of the mean decreases
25. As the sample size increases, the margin of error   decreases
26. As the sample size increases, the variability among the sample means  decreases
27. Exhibit 6-6 The life expectancy of a particular brand of tire is normally distributed with a mean of 40,000 and a standard deviation of 5,000 miles. Refer to Exhibit 6-6. What is the probability that a randomly selected tire will have a life of at least 30,000 miles?  0.9772
28. Exhibit 6-6 The life expectancy of a particular brand of tire is normally distributed with a mean of 40,000 and a standard deviation of 5,000 miles. Refer to Exhibit 6-6. What is the probability that a randomly selected tire will have a life of at least 47,500 miles?  0.0668
29. Exhibit 6-6 The life expectancy of a particular brand of tire is normally distributed with a mean of 40,000 and a standard deviation of 5,000 miles. Refer to Exhibit 6-6. What percentage of tires will have a life of 34,000 to 46,000 miles?   76.98%
30. For a standard normal distribution, a negative value of z indicates   the z is to the left of the mean
31. For the interval estimation of μ when σ is assumed known, the proper distribution to use is the   standard normal distribution
32. For the standard normal probability distribution, the area to the left of the mean is   0.5
33. For which of the following values of p is the value of p(1 − p) maximized?   p = 0.50
34. From a population that is not normally distributed and whose standard deviation is not known, a sample of 50 items is selected to develop an interval estimate for μ. Which of the following statements is true?  The t distribution with 49 degrees of freedom must be used.
35. Given that z is a standard normal random variable, what is the value of z if the area to the right of z is 0.1112?   1.22
36. Given that z is a standard normal random variable, what is the value of z if the area to the right of z is 0.1401?  1.08
37. Given that z is a standard normal random variable, what is the value of z if the area to the left of z is 0.9382?  1.54
38. How many different samples of size 3 (without replacement) can be taken from a finite population of size 10?  120
39. If an interval estimate is said to be constructed at the 90% confidence level, the confidence coefficient would be   0.9
40. If the cost of a Type I error is high, a smaller value should be chosen for the   level of significance
41. If we consider the simple random sampling process as an experiment, the sample mean is  a random variable
42. In determining the sample size necessary to estimate a population proportion, which of the following information is not needed?   the mean of the population
43. In general, higher confidence levels provide  wider confidence intervals
44. In hypothesis testing, the alternative hypothesis is   the hypothesis concluded to be true if the null hypothesis is rejected
45. In hypothesis testing, the hypothesis tentatively assumed to be true is   the null hypothesis
46. In point estimation, data from the  sample is used to estimate the population parameter
47. In tests about a population proportion, p0 represents the   hypothesized population proportion
48. Larger values of the standard deviation result in a normal curve that is   wider and flatter
49. More evidence against H0 is indicated by  smaller p-values
50. Random samples of size 100 are taken from a process (an infinite population) whose population proportion is 0.2. The mean and standard deviation of the distribution of sample proportions are  0.2 and .04
51. Random samples of size 525 are taken from a process (an infinite population) whose population proportion is 0.3. The standard deviation of the sample proportions (i.e., the standard error of the proportion) is  0.0200
52. 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
53. The average life expectancy of tires produced by the Whitney Tire Company has been 40,000 miles. Management believes that due to a new production process, the life expectancy of its tires has increased. In order to test the validity of this belief, the correct set of hypotheses is  H0; μ ≤ 40,000 Ha; μ > 40,000
54. The basis for using a normal probability distribution to approximate the sampling distribution of is  the central limit theorem
55. The confidence associated with an interval estimate is called the   confidence level
56. The expected value of equals the mean of the population from which the sample is drawn  for any sample size
57. The expected value of the random variable is   μ
58. The finite correction factor should be used in the computation of when n/N is greater than  .05
59. The highest point of a normal curve occurs at   the mean
60. The life expectancy of a particular brand of tire is normally distributed with a mean of 40,000 and a standard deviation of 5,000 miles.Refer to Exhibit 6-6. What is the random variable in this experiment?  the life expectancy of this brand of tire
61. The manager of a grocery store has taken a random sample of 100 customers. The average length of time it took these 100 customers to check out was 3.0 minutes. It is known that the standard deviation of the checkout time is one minute. The 95% confidence interval for the average checkout time of all customers is   2.804 to 3.196
62. The number of random samples (without replacement) of size 3 that can be drawn from a population of size 5 is  10
63. 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
64. The population we want to make inferences about is the   target population
65. The probability distribution of all possible values of the sample mean is called the  sampling distribution of the sample mean
66. The probability distribution of all possible values of the sample proportion is the  sampling distribution of p-bar.
67. The probability that the interval estimation procedure will generate an interval that does not contain the actual value of the population parameter being estimated is the   level of significance
68. The purpose of statistical inference is to provide information about the  population based upon information contained in the sample
69. The sample mean is the point estimator of  μ
70. The sample size that guarantees all estimates of proportions will meet the margin of error requirements is computed using a planning value of p equal to   .50
71. The sampling distribution of the sample mean   is the probability distribution showing all possible values of the sample mean
72. The set of all elements of interest in a study is  a population
73. The standard deviation of a point estimator is the   standard error
74. The standard deviation of all possible values is called the  standard error of the mean
75. The standard deviation of is referred to as the  standard error of the proportion
76. The standard deviation of is referred to as the standard error of the mean
77. The t value with a 95% confidence and 24 degrees of freedom is  2.064
78. The value of the ___________ is used to estimate the value of the population parameter.  sample statistic
79. The z value for a 97.8% confidence interval estimation is  2.29
80. 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) which are possible equals  15
81. To compute the minimum sample size for an interval estimate of μ, we must first determine all of the following except   degrees of freedom
82. We can use the normal distribution to make confidence interval estimates for the population proportion, p, when   Both np ≥ 5 and n(1 − p) ≥ 5
83. When the rejection region is in the lower tail of the sampling distribution, the p-value is the area under the curve  less than or equal to the test statistic
84. Which of the following hypotheses applies to a situation where action must be taken both when H0 cannot be rejected and when H0 can be rejected?  H0; mu= mu0
85. Which of the following is an improper form of the null and alternative hypotheses?   H0; μ ≤ μ0 Ha; μ > or = μ0
86. Z is a standard normal random variable. The P (-1.20 ≤ z ≤ 1.50) equals   0.8181
87. Z is a standard normal random variable. The P(1.05 ≤ z ≤ 2.13) equals   0.1303
88. Z is a standard normal random variable. The P(1.20 ≤ z ≤ 1.85) equals   0.0829
89. Z is a standard normal random variable. The P(-1.5 ≤ z ≤ 1.09) equals   0.7953
90. Z is a standard normal random variable. The P(-1.96 ≤ z ≤ -1.4) equals  0.0558
91. Z is a standard normal random variable. The P(z ≥ 2.11) equals  0.0174

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