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UCF QMB 3200 FINAL EXAM COMPLETE 100
QUESTIONS AND CORRECT DETAILED
ANSWERS (VERIFIED ANSWERS) |ALREADY
GRADED A+
Question: Doubling the size of the sample will
ANSWER: reduce the standard error of the mean
Question: The sample mean is the point estimator of
ANSWER: U
Question: A simple random sample of size n from an infinite
population of size N is to be selected. Each possible sample should have
ANSWER: the same probability of being selected
Question: Which of the following statements regarding the
sampling distribution of sample means is incorrect?
ANSWER: The standard deviation of the sampling distribution
is the standard deviation of the population.
Question: A simple random sample of size n from an infinite
population is a sample selected such that
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ANSWER: each element is selected independently and is
selected from the same population
Question: The fact that the sampling distribution of sample
means can be approximated by a normal probability distribution whenever the sample size becomes large is based on the
ANSWER: central limit theorem.
Question: Cluster sampling is
ANSWER: a probability sampling method.
Question: The central limit theorem states that
ANSWER: if the sample size n is large, then the sampling
distribution of the sample mean can be approximated by a normal distribution.
Question: The value of the _____ is used to estimate the value
of the population parameter
ANSWER: sample statistic
Question: The sampling distribution of is the
ANSWER: probability distribution of all possible values of the
sample proportion.
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Question: Which of the following is not a symbol for a
parameter?
ANSWER: S.
Question: The sample statistic characteristic s is the point
estimator of
ANSWER: σ.
Question: The distribution of values taken by a statistic in all
possible samples of the same size from the same population is called a
ANSWER: sampling distribution.
Question: Which of the following is a point estimator?
ANSWER: S.
Question: As a rule of thumb, the sampling distribution of the
sample proportion can be approximated by a normal probability distribution when
ANSWER: n(1 - p) ≥ 5 and np ≥ 5.
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Question: A sample of 92 observations is taken from an infinite
population. The sampling distribution of is approximately
ANSWER: normal because of the central limit theorem.
Question: The central limit theorem is important in Statistics
because it enables reasonably accurate probabilities to be determined for events involving the sample average
ANSWER: when the sample size is large regardless of the
distribution of the variable.
Question: The distribution of values taken by a statistic in all
possible samples of the same size from the same population is the sampling distribution of
ANSWER: The sample
Question: Which of these best describes a sampling distribution
of a statistic?
ANSWER: It is the distribution of all of the statistics calculated
from all possible samples of the same sample size.
Question: The probability distribution of all possible values of
the sample proportion is the