Multiple Choice
Identify the
choice that best completes the statement or answers the question.
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1.
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Following a dramatic drop of 500 points in the Dow
Jones Industrial Average in September 1998, a poll conducted for the Associated Press found that 92%
of those polled said that a year from now their family financial situation will be as good as it is
today or better. The number 92% is a
a. | Statistic | b. | Sample | c. | Parameter | d. | Population | e. | None of the
above. |
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2.
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In a large population, 46% of the households own
VCR’s. A simple random sample of 100 households is to be contacted and the sample
proportion computed. The mean of the sampling distribution of the sample proportion
is
a. | 46 | b. | 0.46 | c. | About 0.46, but
not exactly 0.46 | d. | 0.00248 | e. | The answer cannot
be computed from the information given |
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3.
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If a population has a standard deviation  , then the standard deviation of the mean of 100 randomly selected items from this
population is
a. |  |
b. | 100  |
c. |  /10 |
d. |  /100 |
e. | 0.1 |
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4.
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A statistic is said to be unbiased
if
a. | The survey used to obtain the statistic was designed so
as to avoid even the hint of racial or sexual prejudice | b. | The mean of its sampling distribution is equal to the true value of the
parameter being estimated | c. | Both the person
who calculated the statistic and the subjects whose responses make up the statistic were
truthful | d. | It is used for honest purposes
only | e. | None of the
above. |
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5.
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The number of undergraduates at Johns Hopkins
University is approximately 2000, while the number at Ohio State University is approximately
40,000. At both schools a simple random sample of about 3% of the undergraduates is
taken. Which of the following is the best conclusion?
a. | The sample from Johns Hopkins has less sampling
variability than that from Ohio State. | b. | The sample from
Johns Hopkins has more sampling variability than that from Ohio State. | c. | The sample from Johns Hopkins has almost the same sampling variability as that
from Ohio State. | d. | It is impossible
to make any statement about the sampling variability of the two samples since the students surveyed
were different. | e. | None of the
above. |
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6.
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In a large population, 46% of the households own
VCRs. A simple random sample of 100 households is to be contacted and the sample proportion
computed. What is the standard deviation of the sampling distribution of the sample
proportion?
a. | 46 | b. | 0.46 | c. | 0.00248 | d. | 0.005 | e. | None of the
above. |
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7.
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In a large population of adults, the mean IQ is 112
with a standard deviation of 20. Suppose 200 adults are randomly selected for a market research
campaign. The distribution of the sample mean IQ is
a. | Exactly normal, mean 112, standard deviation
20. | b. | Approximately normal, mean 112, standard deviation
0.1. | c. | Approximately normal, mean 112, standard deviation
1.414. | d. | Approximately normal, mean 112, standard deviation
20. | e. | Exactly normal, mean 112, standard deviation
1.414. |
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8.
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Suppose we are planning on taking an SRS from a
population. If we double the sample size, then  will be multiplied by:
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A factory produces plate glass with a mean
thickness of 4 millimeters and a standard deviation of 1.1 millimeters. A simple random sample of 100
sheets of glass is to be measured, and the sample mean thickness of the 100 sheets 
is to be computed.
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9.
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We know the random variable  has
approximately a normal distribution because of
a. | the law of large numbers. | b. | the central limit theorem. | c. | the law of proportions. | d. | the fact that
probability is the long run proportion of times an event
occurs. |
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10.
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The probability that the average thickness  of the 100 sheets of glass is less than 4.1 millimeters is
approximately
a. | 0.8186. | c. | 0.1814. | b. | 0.3183. | d. | 0.6817. |
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