Saylor URL: http://www.saylor.org/books Saylor.org
inferences about data are probabilistic and never certain—this is why research never “proves” a
theory.
Internal validity refers to the extent to which we can trust the conclusions that have been drawn
about the causal relationship between the independent and dependent variables (Campbell &
Stanley, 1963). [3] Internal validity applies primarily to experimental research designs, in which
the researcher hopes to conclude that the independent variable has caused the dependent variable.
Internal validity is maximized when the research is free from the presence
of confounding variables—variables other than the independent variable on which the
participants in one experimental condition differ systematically from those in other conditions.
Consider an experiment in which a researcher tested the hypothesis that drinking alcohol makes
members of the opposite sex look more attractive. Participants older than 21 years of age were
randomly assigned either to drink orange juice mixed with vodka or to drink orange juice alone.
To eliminate the need for deception, the participants were told whether or not their drinks
contained vodka. After enough time had passed for the alcohol to take effect, the participants
were asked to rate the attractiveness of pictures of members of the opposite sex. The results of
the experiment showed that, as predicted, the participants who drank the vodka rated the photos
as significantly more attractive.
If you think about this experiment for a minute, it may occur to you that although the researcher
wanted to draw the conclusion that the alcohol caused the differences in perceived attractiveness,
the expectation of having consumed alcohol is confounded with the presence of alcohol. That is,
the people who drank alcohol also knew they drank alcohol, and those who did not drink alcohol
knew they did not. It is possible that simply knowing that they were drinking alcohol, rather than
the effect of the alcohol itself, may have caused the differences (see Figure 2.18 "An Example of
Confounding"). One solution to the problem of potential expectancy effects is to tell both groups
that they are drinking orange juice and vodka but really give alcohol to only half of the
participants (it is possible to do this because vodka has very little smell or taste). If differences in
perceived attractiveness are found, the experimenter could then confidently attribute them to the
alcohol rather than to the expectancies about having consumed alcohol.