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

PREVIEW
Most of us spend more time looking down at our mobile
devices than we do looking up at the clouds. But if you
do watch the clouds and have a little imagination, you
occasionally will see them form into familiar shapes.
Figure 8.1 is a photograph of a cloud formation seen over
Kansas City around Christmas in 2008. Do you recognize
a familiar image?
The cloud pattern shown in Figure 8.1 was formed
simply by chance. Specifically, it was the random forces
of wind and air currents that produced a portrait of Santa
Claus. The clouds did not conspire to form the image,
and it was not deliberately created by a team of professional
skywriters. The point we would like to make is
that what appear to be meaningful patterns can be produced
by random chance.
Researchers often find meaningful patterns in the
sample data obtained in research studies. The problem is
deciding whether the patterns found in a sample reflect real
patterns that exist in the population or are simply random,
chance occurrences. To differentiate between real,
systematic patterns and random, chance occurrences,
researchers rely on a statistical technique known as
hypothesis testing, which is introduced in this chapter.
As you will see, a hypothesis test first determines the
probability that the pattern could have been produced
by chance alone. If this probability is large enough, we
conclude that the pattern can reasonably be explained by
chance. However, if the probability is extremely small,
we can rule out chance as a plausible explanation and
conclude that some meaningful, systematic force has
created the pattern. For example, it is reasonable, once
in a lifetime, to see a cloud formation that resembles
Santa Claus. However, it would be extremely unlikely if
the clouds also included the words “Merry Christmas”
spelled out beneath Santa’s face. If this happened, we
would conclude that the pattern was not produced by
the random forces of chance, but rather was created by a
deliberate, systematic act.
In this chapter we introduce the statistical procedure
known as a hypothesis test, which is one of the fundamental
techniques of inferential statistics. In general
terms, a hypothesis test uses the limited information
from a sample to reach a general conclusion about a population.
Specifically, a hypothesis test helps researchers
differentiate between real and random patterns in the
data. We present the logic underlying a hypothesis test,
the terminology used in a hypothesis test, and the general
procedure for conducting a hypothesis test.
FIGURE 8.1
A cloud formation
seen over Kansas City.
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