Cause and Effect

Correlational studies are not uncommon in psychological research. Often,
however, a researcher wants even more specific information about the relationships
among variables—in particular, about whether one variable causes
a change in another variable. In such a situation, experimental research is
warranted. This drawback of the correlational approach—its inability to establish
causal relationships—is worth considering for a moment. In the hypothetical
study described above, the researcher may find that viewing considerable
television violence predicts high levels of aggressive behavior, yet
she cannot conclude that these viewing habits cause the aggressiveness. After
all, it is entirely possible that aggressiveness, caused by some unknown
factor, prompts a preference for violent television. That is, the causal direction
is unknown; viewing television violence may cause aggressiveness, but the inverse (that aggressiveness causes the watching of violent television programs)
is also feasible.
As this is a crucial point, one final illustration is warranted. What if, at a
certain Rocky Mountain university, a correlational study has established that
high levels of snowfall predict low examination scores? One should not conclude
that something about the chemical composition of snow impairs the
learning process. The correlation may be real and highly predictive, but the
causal culprit may be some other factor. Perhaps, as snowfall increases, so
does the incidence of illness, and it is this variable that is causally related to
exam scores. Maybe, as snowfall increases, the likelihood of students using
their study time for skiing also increases.
Experimentation is a powerful research method because it alone can reveal
cause-effect relationships. In an experiment, the researcher does not
merely measure the naturally occurring relationships between variables for
the purpose of predicting one from the other; rather, he or she systematically
manipulates the values of one variable and measures the effect, if any,
that is produced in a second variable. The variable that is manipulated is
known as the independent variable; the other variable, the behavior in question,
is called the dependent variable (any change in it depends upon the
manipulation of the independent variable). Experimental research is characterized
by a desire for control on the part of the researcher. Control of
the independent variable and control over extraneous variables are both
wanted. That is, there is a desire to eliminate or hold constant the factors
(control variables) other than the independent variable that might influence
the dependent variable. If adequate control is achieved, the researcher
may be confident that it was, in fact, the manipulation of the independent
variable that produced the change in the dependent variable.