Cheryl Willard - Lee College

Critical Thinking Concept #2:
Correlation ≠ Causation
Correlation research examines the relationship between two variables. A positive
relationship exists if high scores on one variable are related to high scores on
the other (or if low scores are related to low scores). An example of a positive
correlation would be the amount of time spent studying and scores on an exam.
A negative relationship exists if high scores on one variable are related to low
scores on the other, such as the relationship between the amount of alcohol
consumed and physical coordination skills.
An advantage of the correlation method of research is that it allows for prediction. If
there is a strong correlation between two variables, then knowing the value on one variable
allows us to predict the other. I could predict, for example, that a student who seldom attends
class will do poorly on an exam because there is a negative correlation between class absences
and course grades. However, knowing that a relationship exists does not prove that one variable
is the “cause” of the other. Correlation suggests the possibility of a cause-effect relationship, but
it’s possible that other non-obvious factors may be involved. For example, a negative correlation
has been demonstrated between self-esteem and depression (Myers, 2005). However, the
sources and direction of causation are unknown.
Depression may cause
Low self-esteem may cause
low self-esteem
depression
Self-esteem and depression may influence
each other in a reciprocal fashion
Brain chemistry may cause both
Distressing events may cause both
Depression
low self-esteem
and
depression
low self-esteem
and
depression
low self-esteem
Inferences refer to conclusions or judgments that are made about one thing based on the
observations of something else (Paul & Elder, 2006). This exercise is designed to help students
reason through correlation studies so that the inferences made are logical and justified by the
research methodology.
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