UCF FINAL QMB 3200 EXAM QUESTIONS AND
ANSWERS NEW MODIFIED 2025/2026 NEW
UPDATE
The sampling distribution of is the --ANSWER--probability
distribution of all possible values of the sample proportion.
Which of the following is not a symbol for a parameter? --ANSWER-
-S.
The sample statistic characteristic s is the point estimator of --
ANSWER--σ..
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.
Which of the following is a point estimator? --ANSWER--S.
Page 1 of 39
,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.
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.
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.
Doubling the size of the sample will --ANSWER--reduce the standard
error of the mean
The sample mean is the point estimator of --ANSWER--U
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
Page 2 of 39
,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.
A simple random sample of size n from an infinite population is a
sample selected such that --ANSWER--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 --ANSWER--central limit
theorem.
Cluster sampling is --ANSWER--a probability sampling method.
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.
The value of the _____ is used to estimate the value of the population
parameter --ANSWER--sample statistic
Page 3 of 39
, 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
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.
The probability distribution of all possible values of the sample
proportion is the --ANSWER--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 --ANSWER--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 --ANSWER--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
Page 4 of 39
ANSWERS NEW MODIFIED 2025/2026 NEW
UPDATE
The sampling distribution of is the --ANSWER--probability
distribution of all possible values of the sample proportion.
Which of the following is not a symbol for a parameter? --ANSWER-
-S.
The sample statistic characteristic s is the point estimator of --
ANSWER--σ..
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.
Which of the following is a point estimator? --ANSWER--S.
Page 1 of 39
,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.
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.
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.
Doubling the size of the sample will --ANSWER--reduce the standard
error of the mean
The sample mean is the point estimator of --ANSWER--U
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
Page 2 of 39
,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.
A simple random sample of size n from an infinite population is a
sample selected such that --ANSWER--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 --ANSWER--central limit
theorem.
Cluster sampling is --ANSWER--a probability sampling method.
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.
The value of the _____ is used to estimate the value of the population
parameter --ANSWER--sample statistic
Page 3 of 39
, 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
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.
The probability distribution of all possible values of the sample
proportion is the --ANSWER--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 --ANSWER--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 --ANSWER--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
Page 4 of 39
