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UCF QMB 3200 Final Exam Question and Answers latest 2024

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UCF QMB 3200 Final Exam Question and Answers latest 2024 UCF QMB 3200 Final Exam Question and Answers latest 2024 UCF QMB 3200 Final Exam Question and Answers latest 2024

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UCF QMB 3200 Final Exam Question and
Answers latest 2024
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.



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.



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% confidence is -
ANS 2.576.




In interval estimation, as the sample size becomes larger, the interval estimate - ANS becomes
narrower.In general, higher confidence levels provide larger confidence intervals.



One way to have high confidence and a small margin of error is to - ANS increase the sample size.



From a population that is normally distributed, a sample of 30 elements is selected and the standard
deviation of the sample is computed. For the interval estimation of μ, the proper distribution to use is
the - ANS t distribution with 29 degrees of freedom.

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