UCF QMB 3200 FINAL EXAM TEST
QUESTIONS AND ANSWERS (VERIFIED ANSWERS)
1. 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
2. Which of the following statements regarding the sampling distribution of
sample means is incorrect
ANS The standard deviation of the sampling distributionis the standard
deviation of the population.
3. 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 fromthe same
population
,4. The fact that the sampling distribution of sample means can be approximat-ed
,by a normal probability distribution whenever the sample size becomes large is
based on the
: ANS central limit theorem.
5. The value of the is used to estimate the value of the population
parameter
ANS: sample statistic
6. The sampling distribution of is the
: ANS probability distribution of all possiblevalues of the sample proportion.
7. Which of the following is not a symbol for a parameter
ANS S.
8. The sample statistic characteristic s is the point estimator of
ANS: Ã..
, 9. 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.
10. Which of the following is a point estimator
ANS S.
11. 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) e 5 and np e5.
12. A sample of 92 observations is taken from an infinite population. The
sampling distribution of is approximately
: ANS normal because of the central limittheorem.
13. The central limit theorem is important in Statistics because it enables
reasonably accurate probabilities to be determined for events involving the
sample average
QUESTIONS AND ANSWERS (VERIFIED ANSWERS)
1. 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
2. Which of the following statements regarding the sampling distribution of
sample means is incorrect
ANS The standard deviation of the sampling distributionis the standard
deviation of the population.
3. 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 fromthe same
population
,4. The fact that the sampling distribution of sample means can be approximat-ed
,by a normal probability distribution whenever the sample size becomes large is
based on the
: ANS central limit theorem.
5. The value of the is used to estimate the value of the population
parameter
ANS: sample statistic
6. The sampling distribution of is the
: ANS probability distribution of all possiblevalues of the sample proportion.
7. Which of the following is not a symbol for a parameter
ANS S.
8. The sample statistic characteristic s is the point estimator of
ANS: Ã..
, 9. 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.
10. Which of the following is a point estimator
ANS S.
11. 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) e 5 and np e5.
12. A sample of 92 observations is taken from an infinite population. The
sampling distribution of is approximately
: ANS normal because of the central limittheorem.
13. The central limit theorem is important in Statistics because it enables
reasonably accurate probabilities to be determined for events involving the
sample average
