UCF QMB 3200 FINAL EXAM 2025
QUESTIONS AND ANSWERS
Doubling the size of the sample will - ANS reduce the standard error of the mean
The sample mean is the point estimator of - ANS U
A simple random sample of size n from an infinite population of size N is to be selected. Each
possible sample should have - ANS the same probability of being selected
Which of the following statements regarding the sampling distribution of sample means is
incorrect? - ANS 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 -
ANS 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 -
ANS central limit theorem.
Cluster sampling is - ANS a probability sampling method.
1
Page
@COPYRIGHT SIRJOEL 2025/2026
, The central limit theorem states that - ANS 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 -
ANS sample statistic
The sampling distribution of is the - ANS probability distribution of all possible values of the
sample proportion.
Which of the following is not a symbol for a parameter? - ANS S.
The sample statistic characteristic s is the point estimator of - ANS σ..
The distribution of values taken by a statistic in all possible samples of the same size from the
same population is called a - ANS sampling distribution.
Which of the following is a point estimator? - ANS S.
As a rule of thumb, the sampling distribution of the sample proportion can be approximated by
a normal probability distribution when - ANS n(1 - p) ≥ 5 and np ≥ 5.
A sample of 92 observations is taken from an infinite population. The sampling distribution of is
approximately - ANS 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 - ANS when the
sample size is large regardless of the distribution of the variable.
2
Page
@COPYRIGHT SIRJOEL 2025/2026
, 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 - ANS The sample
Which of these best describes a sampling distribution of a statistic? - ANS 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 -
ANS 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 - ANS 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 - ANS 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? - ANS 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 of pushups that can be done is approximately normal. Which of the
following statements is true? - ANS A t distribution should be used because σ is unknown.
The z value for a 99% confidence interval estimation is - ANS 2.58
In an interval estimation for a proportion of a population, the critical value of z at 99%
3
Page
confidence is - ANS 2.576.
@COPYRIGHT SIRJOEL 2025/2026
QUESTIONS AND ANSWERS
Doubling the size of the sample will - ANS reduce the standard error of the mean
The sample mean is the point estimator of - ANS U
A simple random sample of size n from an infinite population of size N is to be selected. Each
possible sample should have - ANS the same probability of being selected
Which of the following statements regarding the sampling distribution of sample means is
incorrect? - ANS 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 -
ANS 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 -
ANS central limit theorem.
Cluster sampling is - ANS a probability sampling method.
1
Page
@COPYRIGHT SIRJOEL 2025/2026
, The central limit theorem states that - ANS 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 -
ANS sample statistic
The sampling distribution of is the - ANS probability distribution of all possible values of the
sample proportion.
Which of the following is not a symbol for a parameter? - ANS S.
The sample statistic characteristic s is the point estimator of - ANS σ..
The distribution of values taken by a statistic in all possible samples of the same size from the
same population is called a - ANS sampling distribution.
Which of the following is a point estimator? - ANS S.
As a rule of thumb, the sampling distribution of the sample proportion can be approximated by
a normal probability distribution when - ANS n(1 - p) ≥ 5 and np ≥ 5.
A sample of 92 observations is taken from an infinite population. The sampling distribution of is
approximately - ANS 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 - ANS when the
sample size is large regardless of the distribution of the variable.
2
Page
@COPYRIGHT SIRJOEL 2025/2026
, 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 - ANS The sample
Which of these best describes a sampling distribution of a statistic? - ANS 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 -
ANS 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 - ANS 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 - ANS 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? - ANS 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 of pushups that can be done is approximately normal. Which of the
following statements is true? - ANS A t distribution should be used because σ is unknown.
The z value for a 99% confidence interval estimation is - ANS 2.58
In an interval estimation for a proportion of a population, the critical value of z at 99%
3
Page
confidence is - ANS 2.576.
@COPYRIGHT SIRJOEL 2025/2026
