UCF QMB 3200 FINAL EXAM COMPLETE
QUESTIONS WITH VERIFIED ANSWERS
\.Doubling the size of the sample will - ANSWERS✔-reduce the standard error of
the mean
\.The sample mean is the point estimator of - ANSWERS✔-U
\.A simple random sample of size n from an infinite population of size N is to be
selected. Each possible sample should have - ANSWERS✔-the same probability of
being selected
\.Which of the following statements regarding the sampling distribution of sample
means is incorrect? - ANSWERS✔-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 - ANSWERS✔-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 - ANSWERS✔-central limit theorem.
,\.Cluster sampling is - ANSWERS✔-a probability sampling method.
\.The central limit theorem states that - ANSWERS✔-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
- ANSWERS✔-sample statistic
\.The sampling distribution of is the - ANSWERS✔-probability distribution of all
possible values of the sample proportion.
\.Which of the following is not a symbol for a parameter? - ANSWERS✔-S.
\.The sample statistic characteristic s is the point estimator of - ANSWERS✔-σ..
\.The distribution of values taken by a statistic in all possible samples of the same
size from the same population is called a - ANSWERS✔-sampling distribution.
\.Which of the following is a point estimator? - ANSWERS✔-S.
\.As a rule of thumb, the sampling distribution of the sample proportion can be
approximated by a normal probability distribution when - ANSWERS✔-n(1 - p) ≥ 5
and np ≥ 5.
, \.A sample of 92 observations is taken from an infinite population. The sampling
distribution of is approximately - ANSWERS✔-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 -
ANSWERS✔-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 - ANSWERS✔-The
sample
\.Which of these best describes a sampling distribution of a statistic? -
ANSWERS✔-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
- ANSWERS✔-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 -
ANSWERS✔-four times as large as the original sample size.
QUESTIONS WITH VERIFIED ANSWERS
\.Doubling the size of the sample will - ANSWERS✔-reduce the standard error of
the mean
\.The sample mean is the point estimator of - ANSWERS✔-U
\.A simple random sample of size n from an infinite population of size N is to be
selected. Each possible sample should have - ANSWERS✔-the same probability of
being selected
\.Which of the following statements regarding the sampling distribution of sample
means is incorrect? - ANSWERS✔-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 - ANSWERS✔-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 - ANSWERS✔-central limit theorem.
,\.Cluster sampling is - ANSWERS✔-a probability sampling method.
\.The central limit theorem states that - ANSWERS✔-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
- ANSWERS✔-sample statistic
\.The sampling distribution of is the - ANSWERS✔-probability distribution of all
possible values of the sample proportion.
\.Which of the following is not a symbol for a parameter? - ANSWERS✔-S.
\.The sample statistic characteristic s is the point estimator of - ANSWERS✔-σ..
\.The distribution of values taken by a statistic in all possible samples of the same
size from the same population is called a - ANSWERS✔-sampling distribution.
\.Which of the following is a point estimator? - ANSWERS✔-S.
\.As a rule of thumb, the sampling distribution of the sample proportion can be
approximated by a normal probability distribution when - ANSWERS✔-n(1 - p) ≥ 5
and np ≥ 5.
, \.A sample of 92 observations is taken from an infinite population. The sampling
distribution of is approximately - ANSWERS✔-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 -
ANSWERS✔-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 - ANSWERS✔-The
sample
\.Which of these best describes a sampling distribution of a statistic? -
ANSWERS✔-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
- ANSWERS✔-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 -
ANSWERS✔-four times as large as the original sample size.
