Statistics for the Behavioral Sciences by Frederick J. Gravetter, Larry B. Wallnau ISBN 10: 1305504917 ISBN 13: 9781305504912

SECTION 1.2 | Data Structures, Research Methods, and Statistics 13
FIGURE 1.5
Evaluating the relationship
between
variables by comparing
groups of scores.
Note that the values of
one variable are used
to define the groups
and the second variable
is measured to
obtain scores within
each group.
One variable (type of video game)
is used to define groups
A second variable (aggressive behavior)
is measured to obtain scores within each group
Violent
7
8
10
7
9
8
6
10
9
6
Nonviolent
8
4
8
3
6
5
3
4
4
5
Compare groups
of scores
■ Statistics for Comparing Two (or More) Groups of Scores
Most of the statistical procedures presented in this book are designed for research studies
that compare groups of scores like the study in Figure 1.5. Specifically, we examine
descriptive statistics that summarize and describe the scores in each group and we use
inferential statistics to determine whether the differences between the groups can be generalized
to the entire population.
When the measurement procedure produces numerical scores, the statistical evaluation
typically involves computing the average score for each group and then comparing
the averages. The process of computing averages is presented in Chapter 3, and a variety
of statistical techniques for comparing averages are presented in Chapters 8–14. If the
measurement process simply classifies individuals into non-numerical categories, the statistical
evaluation usually consists of computing proportions for each group and then comparing
proportions. Previously, in Table 1.1, we presented an example of non-numerical
data examining the relationship between gender and cell-phone preference. The same data
can be used to compare the proportions for males with the proportions for females. For
example, using text is preferred by 60% of the males compared to 50% of the females. As
before, these data are evaluated using a chi-square test, which is presented in Chapter 17.
■ Experimental and Nonexperimental Methods
There are two distinct research methods that both produce groups of scores to be compared:
the experimental and the nonexperimental strategies. These two research methods use
exactly the same statistics and they both demonstrate a relationship between two variables.
The distinction between the two research strategies is how the relationship is interpreted.
The results from an experiment allow a cause-and-effect explanation. For example, we can
conclude that changes in one variable are responsible for causing differences in a second
variable. A nonexperimental study does not permit a cause-and effect explanation. We can
say that changes in one variable are accompanied by changes in a second variable, but we
cannot say why. Each of the two research methods is discussed in the following sections.
■ The Experimental Method
One specific research method that involves comparing groups of scores is known as the
experimental method or the experimental research strategy. The goal of an experimental
study is to demonstrate a cause-and-effect relationship between two variables. Specifically,