Communication Research: Asking Questions, Finding Answers, 5e (Keyton)
Chapter 10 Testing for Differences
1) Inferential statistics are used to:
A) describe the basic properties of scores.
B) determine the normality of the data.
C) draw conclusions about a population by examining the data from a sample.
D) compute the standard deviation.
E) describe the practical significance of the results.
2) Degrees of freedom:
A) are used to assess the normality of the data.
B) are a way in which researchers account for variation due to error.
C) are the mistakes the researcher admits to in conducting the experiment.
D) the number of participants who did not respond.
E) are the same for all statistical tests.
3) The chi-square:
A) compares the observed frequency with the expected frequency.
B) is best used with continuous level data.
C) tests for differences between two groups.
D) tests for the relationship between two continuous level variables.
E) can test for an interaction effect.
4) In presenting the results for a statistical test of difference, the researcher should report the:
A) statistical test.
B) level of probability or significance achieved.
C) degrees of freedom for the test.
D) null hypothesis.
E) all but D.
5) The t-test is:
A) restricted to one independent variable.
B) restricted to one dependent variable.
C) restricted to two groupings or categories of the independent variable.
D) can test independent or dependent groups.
E) all of the above.
6) When a researcher uses an ANOVA, you can assume that:
A) the independent and dependent variables are both nominal level data.
B) the independent and dependent variables are both continuous level data.
C) the independent variable is nominal level data and the dependent variable is continuous level
data.
D) the independent variable is continuous level data and the dependent variable is nominal level
data.
E) Any of above.
7) Choose the research term that describes the statistical test for determining if differences among
categories are statistically significant.
A) ANOVA
B) chi-square
C) t-test
8) Choose the research term that describes “can test for an interaction effect.”
A) ANOVA
B) chi-square
C) t-test
9) Choose the research term that describes the statistical test for determining differences between
two groups of the independent variable on a continuous level dependent variable.
A) ANOVA
B) chi-square
C) t-test
10) Choose the research term that describes “the data for all variables in this statistical test must be
nominal or categorical.”
A) ANOVA
B) chi-square
C) t-test
11) Choose the research term that describes an extension of the t-test.
A) ANOVA
B) chi-square
C) t-test
12) Choose the research term that describes “two nominal variables are displayed in a contingency
table.”
A) ANOVA
B) chi-square
C) t-test
13) Choose the research term that is represented by X 2.
A) ANOVA
B) chi-square
C) t-test
14) Choose the research term that describes “this test cannot determine casual statements about the
data.”
A) ANOVA
B) chi-square
C) t-test
15) Choose the research term that describes “one independent variable must be a nominal variable
composed of only two groups.”
A) ANOVA
B) chi-square
C) t-test
16) Choose the research term that is represented by the symbol F.
A) ANOVA
B) chi-square
C) t-test
17) Statistical differences can be determined by simply comparing mean scores. If the mean scores
are different, then the difference is statistically significant.
18) The inference that a significant result for a sample will also hold true for the population is
based on the principle of probability.
19) Inferential statistics tell the researcher which participant’s score is the most significant.
20) The null hypothesis is retained until there is sufficient statistical support for accepting the
research hypothesis.
21) It is possible that the difference the researcher predicts in the hypothesis is not the difference
that will exist in the data.
22) In tests of difference, any difference found will be statistically significant.
23) If the test of difference is significant, the research hypothesis is accepted.
24) A chi-square can indicate if significant differences are found, but can not determine where the
significance differences occurred.
25) Chi-squares are limited to testing differences between two levels of any variable.
26) The t-statistic is found by simply computing the means and standard deviations for both
groups.
27) For ANOVA to be statistically significant, the between-groups variance must be greater than
the within-groups variance.
28) Researchers use ANOVA when they are interested in testing for the variance that exists within
groupings of the independent variable.
29) In interpreting an ANOVA, the main effects are ignored if a significant interaction effect
occurs.
30) Explain the difference between random selection of participants and random assignment of
participants.
31) Describe the principles of probability, normal distribution, and random assignment upon
which inferential statistics are based.
32) Explain the difference between a t-test for dependent samples and a t-test for independent
samples.
33) Both t-test and x2 compute a statistic for two groups of scores. Explain the differences between
these two statistical tests.
34) Describe the differences between a two-tailed and one-tailed t-test.
35) Describe the difference between a main effect and an interaction effect. Use examples in your
description.
36) Provide a basic description, and include a diagram, for a 3 × 2 × 2 factorial ANOVA.