Communication Research: Asking Questions, Finding Answers, 5e (Keyton)
Chapter 11 Testing for Relationships
1) If the data for the variables being tested are not normally distributed, the statistical test:
A) cannot be used.
B) is not affected.
C) provides only an approximation of the relationship.
D) must be done on other variables.
E) can control for this by adding additional degrees of freedom.
2) A correlation is the statistical test for:
A) testing the linear relationship between two continuous level variables.
B) testing the linear relationships among three continuous level variables.
C) determining degrees of freedom.
D) determining the significance level of other statistical tests.
E) examining two variables of nominal level data.
3) A spurious correlation is:
A) the relationship between two unrelated variables.
B) a nonsignificant relationship.
C) one in which a third variable influences the nature of the relationship between the two variables
tested.
D) a positive linear relationship.
E) a negative linear relationship.
4) Researchers compute the coefficient of determination to:
A) assess the linear characteristic of the correlation.
B) determine the amount of shared variance for a significant r value.
C) determine the amount of shared variance for a non-significant r value.
D) assess the amount of error in a statistical test.
E) determine if the correlation is positive or negative.
5) A correlation matrix is used to:
A) display how every variable is correlated with every other variable.
B) display the shared variance between pairs of variables.
C) identify all of the possible hypotheses in a research study.
D) determine which relationships are significant and worthy of further study.
E) none of the above.
6) A correlation of .70 is interpreted as:
A) a negative correlation.
B) demonstrating a weak relationship between two variables.
C) is stronger than a correlation of -.70.
D) being correct about 70% of the time.
E) none of the above.
7) Regression is superior to correlation because it:
A) is more flexible.
B) can predict some variables by knowing others.
C) can be used when there are two or more independent, or predictor, variables.
D) can test for the influence of more than one independent variable.
E) all of the above.
8) Exogenous variables are:
A) Used in structural equation modeling (SEM)
B) Also known as endogenous variables
C) Variables that are not caused by another variable
D) Variables that are caused by another variable
E) Both A and C.
9) Tests for relationship are most commonly computed for variables of continuous level data.
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10) Statistical tests for relationship are limited to two variables.
11) Researchers use inferential statistics to determine if the relationship observed in the data is
stronger than the relationship that might occur due to chance.
12) Statistical tests were designed to test for relationships and differences on normally distributed
variables.
13) The significance level is usually set at .05 as the criterion for making the decision to accept the
research hypothesis.
14) Regardless of how the research hypothesis is stated, there is a complementary null hypothesis.
15) To use a correlation as a statistical test, each participant must have provided measurements on
two separate variables.
16) Correlation equals causation.
17) A correlation coefficient can range from -1.00 to +1.00.
18) Correlation tests for curvilinear relationships.
19) A significant r value would cause the researcher to retain the null hypothesis.
20) Regression is of particular advantage to communication researchers because it allows
researchers to study variables that cannot be experimentally manipulated.
21) Because there is no theoretical limit to the number of predictor variables tested in multiple
regression, it is common for researchers to include 10 or more.
22) Multiple regression allows the researcher to determine the relative importance of each variable
to the regression relationship.
23) Statistically significant results ensure practical application of the results.
24) Explain why statistical tests are designed to test the scores of a sample, rather than the scores of
one individual participant.
25) Describe how the researcher interprets a correlation if the .05 significance level is not
achieved.
26) Describe the steps the researcher takes to interpret the regression statistic once it can be
determined that the test is significant.
27) Describes the steps in interpreting a correlation coefficient.
28) Describe the limitations of correlation as a statistical test.
29) Explain the phrase “variance accounted for” as it would be used with a test of regression.
30) Describe the basic difference between a simple linear regression and multiple regression.