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UCF QMB 3200 Final Exam Completed Updated Version with All Questions and 100% Correct Answers
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UCF QMB 3200 Final Exam Completed Updated Version with All Questions and 100% Correct Answers
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UCF QMB 3200 Final ExamUCF QMB 3200 Final
Exam
, UCF QMB 3200 Final Exam
1. Doubling the size of the sample will:
reduce the standard error of the mean
2. The sample mean is the point estimator of:
U
3. 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
4. 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.
5. A simple random sample of size n from an infinite population is a sample
selected such that:
, UCF QMB 3200 Final Exam
each element is selected independently and is selected from the same
population
6. 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:
central limit theorem.
7. Cluster sampling is:
a probability sampling method.
8. 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.
9. The value of the _____ is used to estimate the value of the population
parameter: sample statistic
10. The sampling distribution of is the: probability distribution of all possib
values of the sample proportion.
, UCF QMB 3200 Final Exam
11. Which of the following is not a symbol for a parameter?: S.
12. The sample statistic characteristic s is the point estimator of: Ã..
13. The distribution of values taken by a statistic in all possible samples of th
same size from the same population is called a: sampling distribution.
14. Which of the following is a point estimator?: S.
15. As a rule of thumb, the sampling distribution of the sample proportion ca
be approximated by a normal probability distribution when: n(1 - p) e 5 an
np e 5.
16. A sample of 92 observations is taken from an infinite population. Th
sampling distribution of is approximately: normal because of the central lim
theorem.
17. The central limit theorem is important in Statistics because it enable
reasonably accurate probabilities to be determined for events involvin
the sample average: when the sample size is large regardless of th
distribution of the variable.
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