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| 1.
|  |  The results of a scientific poll showed that 64 out of 400 patients at a certain hospital are not satisfied with the care they received in the hospital after major surgery. A consumer advocate claims that 20% of the major surgery patients at the hospital are dissatisfied with after-surgery care. If the advocate's claim is true, what is the probability that 64 or fewer of 400 randomly selected patients at the hospital would say they are dissatisfied with the after-surgery care? |
|  | A) | 47.72% |
|  | B) | 2.28% |
|  | C) | 97.72% |
|  | D) | 95.44% |
|  | E) | 4.56% |
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| 2.
|  |  For non-normal populations, as the sample size (n) _________________, the distribution of sample means approaches a/an ___________________ distribution. |
|  | A) | decreases, uniform |
|  | B) | increases, normal |
|  | C) | decreases, normal |
|  | D) | increases, uniform |
|  | E) | increases, exponential |
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| 3.
|  |  As the sample size _____________ the variation of the sampling distribution of  (1.0K) __________________. |
|  | A) | decreases, decreases |
|  | B) | increases, remains the same |
|  | C) | decreases, remains the same |
|  | D) | increases, decreases |
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| 4.
|  |  If the sampled population has mean 48 and standard deviation 16, then the mean and the standard deviation for the sampling distribution of  (1.0K) for n = 16 are |
|  | A) | 4 and 1. |
|  | B) | 12 and 4. |
|  | C) | 48 and 4. |
|  | D) | 48 and 1. |
|  | E) | 48 and 16. |
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| 5.
|  |  A manufacturing company measures the weight of boxes before shipping them to the customers. If the box weights have a population mean and standard deviation of 90 lbs and 24 lbs respectively, then, based on a sample size of 36 boxes, the probability that the average weight of the boxes will be less than 84 lbs is |
|  | A) | 16.87%. |
|  | B) | 93.32%. |
|  | C) | 43.32%. |
|  | D) | 6.68%. |
|  | E) | 84.13%. |
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| 6.
|  |  Whenever the sampled population has a normal distribution, the sampling distribution of  (1.0K) is a normal distribution |
|  | A) | for only large sample sizes. |
|  | B) | for only small sample sizes. |
|  | C) | for any sample size. |
|  | D) | for only samples of size 30 or more. |
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| 7.
|  |  If in a sampling distribution of  (1.0K) the sample size is 25, what assumption must hold for the sampling distribution of  (1.0K) to be normal? |
|  | A) | Population distribution is normal. |
|  | B) |  (1.0K). |
|  | C) | Population distribution is uniform |
|  | D) |  (1.0K). |
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| 8.
|  |  The sampling distribution of  (1.0K) must be a normal distribution with a mean 0 and standard deviation 1. |
|  | A) | True |
|  | B) | False |
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| 9.
|  |  A sample statistic is an unbiased point estimate of a population parameter if the mean of the population of all possible values of the statistic equals the population parameter. |
|  | A) | True |
|  | B) | False |
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| 10.
|  |  The standard deviation of all possible sample proportions increases as the sample size increases. |
|  | A) | True |
|  | B) | False |
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| 11.
|  |  The central limit theorem states that as sample size increases, the population distribution more closely approximates a normal distribution. |
|  | A) | True |
|  | B) | False |
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| 12.
|  |  If the population proportion is . 4 with a sample size of 20, then this sample is large enough so that the sampling distribution of  (0.0K) is a normal distribution. |
|  | A) | True |
|  | B) | False |
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