Test Bank
How To Use SPSS Statistics, 9th Ed.
Chapter 8: Nonparametric Inferential Statistics
1. Which of the following are TRUE about a chi-square Goodness of Fit Test?
I. The GOF test can compare sample proportions to theoretical values.
II. You could use the GOF test compare blood type breakdown as published by
the American Red Cross to the blood collected at a recent blood drive.
III. If you perform a chi-square GOF test, you should also calculate a mean and
standard deviation.
IV. There are no assumptions about the shape of the distribution.
a. I & II only
b. I & III only
2. Which of the following is FALSE?
d. A significant chi-square test indicates that the data vary from the expected values.
e. A test that is not significant indicates that the data are consistent with the expected
values.
3. Which of the following are TRUE?
I. A chi-square test of independence is essentially the nonparametric version
of the interaction term in ANOVA.
II. A chi-square test of independence requires more than two variables.
III. Expected cell frequencies should all be less than 1.
IV. No more than 20% of the categories should have less than 5 expected
frequencies.
V. Two variables are independent if knowing the outcome of one tells you
nothing about the outcome of the other.
VI. Two variables are independent if knowing the outcome of one tells
you something about the outcome of the other.
a. I, II, & III only
b. II, III, IV only
4. Which piece of information in the following summary is INCORRECT?
“A chi-square test of independence was calculated comparing the
frequency of incarceration of African Americans with that of Caucasians.
A significant interaction was found (𝜒2(1) = 26.03, p < 0.05). African
Americans were almost 6 times less likely to be incarcerated (2.21%)
than Caucasians (0.38%).”
a. test of independence
5. Which statement is INCORRECT?
d. A Wilcoxon test indicates whether two related samples are different in terms of their
ranks.
e. A Kruskal-Wallis H test is the nonparametric equivalent of the one-way ANOVA.
f. A Friedman test is the nonparametric equivalent of the one-way repeated-measures
ANOVA.
6. Nonparametric inferential statistics:
I. are used when the corresponding parametric procedure is inappropriate.
II. are preferred over parametric inferential statistics.
III. have very few assumptions.
a. I
7. Most of the nonparametric tests use the following click sequence:
a. File → Nonparametric Tests
b. Edit → Nonparametric Tests
For the following questions, match each procedure with one of the descriptions below.
a. Evaluates whether the medians of a test variable differ significantly between two
independent groups.
b. Evaluates the differences in medians across all levels of factor (i.e., grouping
variable).
c. Evaluates whether the proportion of individuals who fall into categories of a
variable are equal to hypothesized values
d. Evaluates the differences between paired scores on the rankings of a test
variable.
e. Evaluates the differences between repeated paired scores on the rankings of a
test variable.
f. Evaluates whether two variables are independent of each other.