I highlighted the answers that I know for sure are correct, but it can still help to
know the questions can find the answers. Chegg website had a lot of the answers
but I do not have a membership to see the answers. If you get one you will see
most of the questions on there.
Question 1
What must be done to decrease the chances of Type I and Type II errors?
Answers
:
a.
Increase the sample size.
b.
Decrease the sample size.
c.
Decrease the number of variables.
d.
Measure the sample characteristics
Response Feedback:
page 521
Question 2
Which statement is true about chi-square analysis?
Answers
:
a.

It is a parametric test.
b.
It is used for two nominal variables
c.
It has the assumption of a normal distribution
Response Feedback:
page 575
Question 3
Which of the following measures is the most helpful both for providing a
quantification of dispersion and for providing a way to interpret how far away from
the mean each individual score is?
Answers:
a.
Range
b.
Difference scores
c.
Magnitude
d.
Standard deviation

Response Feedback:
page 540
Question 4
A group of 15 nurses was asked which of two types of coffee they preferred. Seven of
the nurses preferred the first type, while eight of the nurses preferred the second type.
Which statistical test would be appropriate to determine differences in these two
groups?
Answers
:
a.
paired
t
-test
b.
Chi-square
c.
parametric test
Response Feedback:
page 576
Question 5
Which of the following correlation coefficients shows the strongest relationship?
Answers
:
a.
.10
b.

.80
c.
–.85
Response Feedback:
page 546
Question 6

Question 7
Which of the following tests is essentially a comparison of means?
Answers
:
a.
Pearson's correlation
b.
Chi-square
c.
t-
test
Response
Feedback:
One of the most common parametric analyses used to test for
significant differences between group means of two samples is the
t-
test. In its calculation, the numerator is the difference scores of the
means of the two samples. In addition, the test uses the pooled
standard deviation of the two samples as the denominator.

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- Fall '16
- Denise Cauble
- Nursing, Statistics, researcher, Statistical significance, Response Feedback