ACCURACY IS GUARANTEED
UCF QMB 3200 Final Exam Questions with
Detailed Verified Answers for Accuracy
Doubling the size of the sample will
✓✓ reduce the standard error of the mean
The sample mean is the point estimator of
✓✓ U
A simple random sample of size n from an infinite population
of size N is to be selected. Each possible sample should have
✓✓ the same probability of being selected
Which of the following statements regarding the sampling
distribution of sample means is incorrect?
✓✓ The standard deviation of the sampling distribution is the
standard deviation of the population.
A simple random sample of size n from an infinite population
is a sample selected such that
✓✓ each element is selected independently and is selected from
the same population
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
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✓✓ central limit theorem.
Cluster sampling is
✓✓ a probability sampling method.
The central limit theorem states that
✓✓ if the sample size n is large, then the sampling distribution
of the sample mean can be approximated by a normal
distribution.
The value of the _____ is used to estimate the value of the
population parameter
✓✓ sample statistic
The sampling distribution of is the
✓✓ probability distribution of all possible values of the sample
proportion.
Which of the following is not a symbol for a parameter?
✓✓ S.
The sample statistic characteristic s is the point estimator of
✓✓ σ..
The distribution of values taken by a statistic in all possible
samples of the same size from the same population is called a
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✓✓ sampling distribution.
Which of the following is a point estimator?
✓✓ S.
As a rule of thumb, the sampling distribution of the sample
proportion can be approximated by a normal probability
distribution when
✓✓ n(1 - p) ≥ 5 and np ≥ 5.
A sample of 92 observations is taken from an infinite
population. The sampling distribution of is approximately
✓✓ normal because of the central limit theorem.
The central limit theorem is important in Statistics because it
enables reasonably accurate probabilities to be determined for
events involving the sample average
✓✓ when the sample size is large regardless of the distribution
of the variable.
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
✓✓ The sample
Which of these best describes a sampling distribution of a
statistic?
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✓✓ It is the distribution of all of the statistics calculated from
all possible samples of the same sample size.
The probability distribution of all possible values of the sample
proportion is the
✓✓ sampling distribution of p.
For a fixed confidence level and population standard deviation,
if we would like to cut our margin of error in half, we should
take a sample size that is
✓✓ four times as large as the original sample size.
We can reduce the margin of error in an interval estimate of p
by doing any of the following except
✓✓ increasing the planning value p* to .5.
When computing the sample size needed to estimate a
proportion within a given margin of error for a specific
confidence level, what planning value of p should be used when
no estimate of p is available?
✓✓ 0.50
A statistics teacher started class one day by drawing the names
of 10 students out of a hat and asked them to do as many
pushups as they could. The 10 randomly selected students
averaged 15 pushups per person with a standard deviation of 9
pushups. Suppose the distribution of the population of number
UCF QMB 3200 Final Exam Questions with
Detailed Verified Answers for Accuracy
Doubling the size of the sample will
✓✓ reduce the standard error of the mean
The sample mean is the point estimator of
✓✓ U
A simple random sample of size n from an infinite population
of size N is to be selected. Each possible sample should have
✓✓ the same probability of being selected
Which of the following statements regarding the sampling
distribution of sample means is incorrect?
✓✓ The standard deviation of the sampling distribution is the
standard deviation of the population.
A simple random sample of size n from an infinite population
is a sample selected such that
✓✓ each element is selected independently and is selected from
the same population
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
, ACCURACY IS GUARANTEED
✓✓ central limit theorem.
Cluster sampling is
✓✓ a probability sampling method.
The central limit theorem states that
✓✓ if the sample size n is large, then the sampling distribution
of the sample mean can be approximated by a normal
distribution.
The value of the _____ is used to estimate the value of the
population parameter
✓✓ sample statistic
The sampling distribution of is the
✓✓ probability distribution of all possible values of the sample
proportion.
Which of the following is not a symbol for a parameter?
✓✓ S.
The sample statistic characteristic s is the point estimator of
✓✓ σ..
The distribution of values taken by a statistic in all possible
samples of the same size from the same population is called a
, ACCURACY IS GUARANTEED
✓✓ sampling distribution.
Which of the following is a point estimator?
✓✓ S.
As a rule of thumb, the sampling distribution of the sample
proportion can be approximated by a normal probability
distribution when
✓✓ n(1 - p) ≥ 5 and np ≥ 5.
A sample of 92 observations is taken from an infinite
population. The sampling distribution of is approximately
✓✓ normal because of the central limit theorem.
The central limit theorem is important in Statistics because it
enables reasonably accurate probabilities to be determined for
events involving the sample average
✓✓ when the sample size is large regardless of the distribution
of the variable.
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
✓✓ The sample
Which of these best describes a sampling distribution of a
statistic?
, ACCURACY IS GUARANTEED
✓✓ It is the distribution of all of the statistics calculated from
all possible samples of the same sample size.
The probability distribution of all possible values of the sample
proportion is the
✓✓ sampling distribution of p.
For a fixed confidence level and population standard deviation,
if we would like to cut our margin of error in half, we should
take a sample size that is
✓✓ four times as large as the original sample size.
We can reduce the margin of error in an interval estimate of p
by doing any of the following except
✓✓ increasing the planning value p* to .5.
When computing the sample size needed to estimate a
proportion within a given margin of error for a specific
confidence level, what planning value of p should be used when
no estimate of p is available?
✓✓ 0.50
A statistics teacher started class one day by drawing the names
of 10 students out of a hat and asked them to do as many
pushups as they could. The 10 randomly selected students
averaged 15 pushups per person with a standard deviation of 9
pushups. Suppose the distribution of the population of number
