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QMB 3200 EXAM 1 UCF Chapter 7 Questions and Answers.docxQMB 3200 EXAM 1 UCF Chapter 7 Questions and Answers.docx

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QMB 3200 EXAM 1 UCF Chapter 7 Questions and A

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QMB 3200 EXAM 1 UCF Chapter 7
Questions and Answers
The central limit theorem is important in Statistics because it -
correct answer ✅enables reasonably accurate probabilities to be
determined for events involving the sample average when the
sample size is large regardless of the distribution of the variable.


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: -
correct answer ✅central limit theorem.


Sample statistics, such as x̅ , s, or p̅, that provide the point estimate
of the population parameter are known as: -
correct answer ✅Point Estimators


As a rule of thumb, the sampling distribution of the sample
proportion can be approximated by a normal probability
distribution when: -
correct answer ✅n(1 - p) ≥ 5 and np ≥ 5.


Which of the following statements regarding the sampling
distribution of sample means is incorrect?

, QMB 3200 EXAM 1 UCF Chapter 7
Questions and Answers
The mean of the sampling distribution is the mean of the
population.


The sampling distribution is approximately normal when the
population is normal or the sample size is sufficiently large.


The sampling distribution is found by taking repeated samples of
the same size from the population of interest and computing the
mean of each sample.


The standard deviation of the sampling distribution is the standard
deviation of the population. -
correct answer ✅The standard deviation of the sampling
distribution is the standard deviation of the population.


As the sample size increases, the: -
correct answer ✅standard error of the mean decreases


The sample mean is the point estimator of: -
correct answer ✅μ

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