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UCF QMB 3200 Final Exam Questions And Answers Latest Update
- Course
- QMB 3200
- Institution
- University Of Central Florida
UCF QMB 3200 Final Exam Questions And Answers Latest Update
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Solution 2024/2025Pepper
UCF QMB 3200 Final Exam Questions And Answers Latest Update
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.
, Solution 2024/2025
Pepper
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.
, Solution 2024/2025
Pepper
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.
As the number of degrees of freedom for a t distribution increases, the difference between the t distribution and the
standard normal distribution ANS✔✔ becomes smaller.
The value added and subtracted from a point estimate in order to develop an interval estimate of the population
parameter is known as the ANS✔✔ margin of error.
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