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      Figure 3.5 Scatterplot Diagrams of Different Relationships and Their Corresponding r Value

      Source: Landis, R. S. (2007). Measures of association/correlation coefficient. In S. G. Rogelberg (Ed.), Encyclopedia of industrial and organizational psychology (pp. 471–474, Figure 1). Thousand Oaks, CA: SAGE.

      My colleagues and I used a correlational technique to understand whether being tortured influenced the brain differently if one experienced dissociative experiences, in which one feels detached from reality (Ray et al., 2006). Although not much is known concerning neuroscience measurements of individuals who have been tortured in their native country, there has been some suggestion that torture leads to different types of psychopathological disorders. There is also some evidence to suggest that torture victims adopt psychological mechanisms to escape the experience of the situation. Dissociation is one such mechanism in which individuals are able to distance themselves from such extreme negative experiences as torture or rape. We developed a dissociative scale that asked individuals about dissociative experiences they had experienced. Since some other neuroscience work had shown that non-normal MEG (magnetoencephalography) activity was seen in different areas of the brain in disorders such as schizophrenia, depression, and PTSD (e.g., Rockstroh, Wienbruch, Ray, & Elbert, 2007), we used MEG as the variable to correlate with dissociative experiences. We found a positive correlation of .60 between our measure of MEG activity and the dissociation scale for the left hemisphere as a whole and a negative correlation of -.61 for the right hemisphere as a whole. More precise analysis showed the involvement of the left ventral region of the anterior cortical areas.

      What we cannot know from correlational research is whether either variable influences the other directly. There are a variety of ways that one can see a high correlation. It might be that there is a direct relationship. That is, having lots of friends might make you feel better and make you less susceptible to disease. However, it might also be true that if you went to the health center often, you might not have time for friends or not feel like being with others. In our torture study, one might logically assume that the torture influenced the brain. However, it might have been the case that those individuals who had particular types of MEG activity would be those that later developed dissociative experiences.

      It is also possible that a third unspecified variable actually may have influenced the two variables in a correlational study. For example, there is a strong correlation between eating ice cream and wearing bathing suits. However, in this case it is a third variable, the warm weather, which produces the relationship. In the case of health and friends, it could be genetic makeup or having a job, both of which could influence the time one had for friends as well as health. Thus, the nature of a correlational study is to describe the relationships but not to suggest which variable influences which other variable.

      It is often said that correlation does not imply causality. For example, a researcher might want to know whether a relationship exists between the type of food a child eats and the likelihood of the child having a particular mental disorder such as hyperactivity. One approach would be to examine the diets of children who show hyperactivity and those who do not. What if there was a high association between eating foods with sugar, for example, and hyperactivity? You could conclude little other than that there was an association or correlation between the two variables. There are at least three ways to understand this relationship. (1) It might be that sugar is associated with hyperactivity. (2) It might also be that those who are hyperactive seek sugar. (3) A third variable such as a specific gene or neurotransmitter or sleep pattern might lead to both eating foods with sugar and showing hyperactivity.

      The association of two factors does not in itself imply that one influences the other. However, if there is a low correlation between the events, you can infer that one event does not cause the other. A high degree of association is always necessary for establishing that one variable influences another; a correlational study is often the first step to providing the needed support for later experimental research, especially in complex areas.

      Concept Check

      The Experimental Method: Making It Happen

      Just finding that a relationship exists between two events does not allow us to determine exactly what that relationship is, much less that one event actually caused the other to happen. If we want to state that one event produced another event, we need to develop a much stronger case for our position.

      To do this, we could see how some single event over which we have control affects the phenomenon we are studying. In this way, we begin to interact with the phenomenon. We structure our question in this form: If I do this, what will happen? Numerous questions can be asked in this way, such as, Will people with depression learn words better in a foreign language if each word is of the same class (e.g., negative emotional words) than if they are from a variety of different classes (some emotional, some objects, some neutral words)?

      experimental method: scientific research technique in which the influence of an independent variable (IV) on a dependent variable (DV) is determined, using carefully structured conditions

      As our knowledge grows, we may even get to the point of formulating specific predictions. In particular, our questions are structured in this form: If I do this, I expect this will happen. Sometimes our predictions are more global, and we predict that one factor will be stronger than another. We might predict that more people are likely to help a stranger if they perceive the environment to be safe than if they think it is dangerous. At other times, however, we may know enough about an area to make a more precise prediction or point prediction. For example, we might predict that 3 months of exercise will lead to a drop in self-reported depression on a standard scale. These approaches, in which we interact directly with the phenomenon we are studying, are examples of the experimental method.

      Definitions in the Experimental Method

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