Question 1.1. What is the probability of type II error when
the null hypothesis is rejected?
0.5
0.05
0.025
0
Question 2.2. According to the central limit theorem, a
population which is skewed to begin with will still be skewed when it is
re-formed as a distribution of sample means. (Points : 1)
True
False
Question 3.3. Which of the following is a provision of the
central limit theorem? (Points : 1)
A skewed
distribution will remain skewed however it is plotted.
There are
limits to the range of scores that can be fitted to a distribution.
A distribution
based on sample means will be normal.
There will
always be theoretical differences between distributions.
Question 4.4. What is the relationship between the power of
a statistical test and decision errors?
@Answer found in section 4.3 The One-sample t-Test, in
Statistics for Managers (Points : 1)
Powerful tests
minimize the risk of decision errors.
Powerful tests
are more inclined to type II than type I errors.
Powerful tests
compensate for decision errors with stronger effect sizes.
Powerful tests
minimize type II errors.
Question 5.5. Why do the critical values change with degrees
of freedom for the t-tests?
@Answer found in section 4.3 The One-sample t-Test, in
Statistics for Managers
(Points : 1)
Different
degrees of freedom define different t distributions.
Because the
critical values are calculated directly from degrees of freedom.
The degrees of
freedom reflect the value of SEM.
The degrees of
freedom are indexed to the M – µM difference.
Question 6.6. The standard error of the mean can be
calculated by dividing µ by the square root of the number of values in the
distribution. (Points : 1)
True
False
Question 7.7. If a certifying agency raises the requirements
for real estate agents, what sort of decision error is the agency protecting
against? (Points : 1)
Type I
Type II
Type III
Type IV
Question 8.8. Statistical significance for a tested mean
difference means practical significance as well. (Points : 1)
True
False
Question 9.9. The standard error of the mean is actually the
standard deviation of all of the means that make up the distribution of sample
means. (Points : 1)
True
False
Question 10.10. What is the alternate hypothesis in a
problem where sales group two is predicted to be “. . . significantly less
productive than sales group one?”
@Answer found in sections 4.3 The One-sample t-Test and 4.4
Hypothesis Testing, in Statistics for Managers (Points : 1)
HA: µ1
? µ 2
HA: µ 1= µ 2
HA: µ 1> µ2
HA: µ 1< µ 2
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