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| 1 | |
The mean of the sampling distribution of the sample mean is: |
| | A) | equal to the mean of the population. |
| | B) | an approximation of the mean of the population. |
| | C) | not a good estimate of the population mean. |
| | D) | equal to the population mean divided by n. |
| | E) | none of the above. |
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| 2 | |
A 99% confidence interval can be interpreted as: |
| | A) | In 99% of the samples, the mean of the samples will be outside the interval. |
| | B) | There is a 1% chance that the true parameter value is outside the interval. |
| | C) | 99% of all population values are within the interval. |
| | D) | Both a and b. |
| | E) | None of the above. |
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| 3 | |
Upper and lower interval limits for a 90% confidence interval for μ are, respectively, 180 cm and 220 cm. We would infer from these limits a __________ likelihood that __________. |
| | A) | 5%; μ is no more than 220 cm |
| | B) | 95%; μ is no more than 180 cm |
| | C) | 90%; the interval from 180 cm to 220 cm contains the true population mean μ |
| | D) | Only A and B are correct |
| | E) | A, B & C are correct |
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| 4 | |
When the sample size increases, everything else remaining the same, the width of a confidence interval for a population parameter will: |
| | A) | increase |
| | B) | decrease |
| | C) | remain unchanged |
| | D) | sometimes increase and sometimes decrease |
| | E) | impossible to tell |
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| 5 | |
If the population standard deviation is not known, what should be used as a point estimate? |
| | A) | The standard deviation of a few sample means. |
| | B) | The sample mean. |
| | C) | The sample standard deviation. |
| | D) | Any of the above. |
| | E) | None of the above. |
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| 6 | |
If the sample size is cut to 1/4 of its present size, all else being the same, the confidence interval will become: |
| | A) | twice as wide |
| | B) | half as wide |
| | C) | four times as wide |
| | D) | will not change |
| | E) | not enough information to determine |
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| 7 | |
If we want to construct a confidence interval half as wide as the current one, then the sample needs to be: |
| | A) | twice as large |
| | B) | half as large |
| | C) | four times as large |
| | D) | eight times as large |
| | E) | one-fourth as large |
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| 8 | |
For n = 121, sample mean = 96, and a known population standard deviation σ = 14, construct a 95% confidence interval for the population mean. |
| | A) | [93.53, 98.48] |
| | B) | [93.51, 98.49] |
| | C) | [93.02, 98.98] |
| | D) | [93.06, 98.94] |
| | E) | [93.00, 98.95] |
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| 9 | |
A 95% confidence interval for μ is being formulated based on a sample of 16. What is the appropriate value for t? |
| | A) | 1.746 |
| | B) | 2.120 |
| | C) | 2.131 |
| | D) | 2.473 |
| | E) | 2.490 |
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| 10 | |
The sample mean is 115, the sample size is 16, and the sample standard deviation is 4. Construct a 99% confidence interval for the population mean. |
| | A) | [113.04, 116.96] |
| | B) | [112.425, 117.575] |
| | C) | [112.053, 117.947] |
| | D) | [112.869, 117.131] |
| | E) | none of the above |
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| 11 | |
A 99% confidence interval for s2 is being formulated based on a sample of 16 observations. What are appropriate values for χ2? |
| | A) | χ2Lower = 4.07; χ2Upper = 34.95 |
| | B) | χ2Lower = 4.07; χ2Upper = 31.32 |
| | C) | χ2Lower = 4.60; χ2Upper = 32.80 |
| | D) | χ2Lower = 5.14; χ2Upper = 34.27 |
| | E) | χ2Lower = 5.23; χ2Upper = 30.58 |
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| 12 | |
A confidence interval for the population variance is being formulated, and a random sample of 35 observations yields a sample variance &sigma2 = 2,120. What would interval limits for σ2 be if a 95% confidence interval was desired? |
| | A) | 1,483.1, 3,327.8 |
| | B) | 1,387.0, 3,638.6 |
| | C) | 1,308.4, 3,951.8 |
| | D) | 1,227.5, 4,368.5 |
| | E) | 1,167.5, 4,689.7 |
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