UCF QMB 3200 Final Exam Verified Questions with Correct Answers Graded A+
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UCF QMB 3200
UCF QMB 3200 Final Exam Verified Questions with Correct Answers Graded A+
Doubling the size of the sample will
reduce the standard error of the mean
The sample mean is the point estimator of
U
A simple random sample of size n from an infinite population of size N is to be selected. Each possib...
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UCF QMB 3200 Final Exam Verified Questions with Correct
Answers Graded A+
Doubling the size of the sample will
reduce the standard error of the mean
The sample mean is the point estimator of
U
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
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.
A simple random sample of size n from an infinite population is a sample selected such that
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
central limit theorem.
Cluster sampling is
a probability sampling method.
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.
The value of the _____ is used to estimate the value of the population parameter
sample statistic
The sampling distribution of is the
probability distribution of all possible values of the sample proportion.
Which of the following is not a symbol for a parameter?
S.
The sample statistic characteristic s is the point estimator of
σ..
,The distribution of values taken by a statistic in all possible samples of the same size from the same
population is called a
sampling distribution.
Which of the following is a point estimator?
S.
As a rule of thumb, the sampling distribution of the sample proportion can be approximated by a normal
probability distribution when
n(1 - p) ≥ 5 and np ≥ 5.
A sample of 92 observations is taken from an infinite population. The sampling distribution of is
approximately
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
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
The sample
Which of these best describes a sampling distribution of a statistic?
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
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
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
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?
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?
A t distribution should be used because σ is unknown.
The z value for a 99% confidence interval estimation is
2.58
In an interval estimation for a proportion of a population, the critical value of z at 99% confidence is
2.576.
In interval estimation, as the sample size becomes larger, the interval estimate
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
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
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
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
margin of error.
What is the symbol for the population mean? If the population follows a normal distribution, the
confidence interval is _____ and can be used for any sample size. If the population does not follow a
normal distribution, the confidence interval will be _____. Which of the following choices correctly
complete this statement?
exact; approximate.
The t value for a 99% confidence interval estimation based upon a sample of size 10 is
3.250.
To compute the necessary sample size for an interval estimate of a population proportion, all of the
following procedures are recommended when p is unknown except
using .95 as an estimate.
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