Correlation and causation are two important concepts. It is important to understand the difference between correlation vs. causation. With respect to research findings, if there is a significant correlation between two things it is merely stating that we can predict one thing from the other. We can predict variables without knowing if they are casually related. Thus, the use of the word "correlation" does not mean causation.
Correlation Interpretation
If A and B are correlated, it could indicate that A caused B, B caused A, or a third variable caused both A and B. Two things can be correlated without there being a casual relationship.
Correlation Examples
There are many possible correlation examples. One example of a correlation is the association between a supervisor's perceived humor and job satisfaction. Decker (1987) found that a supervisor's perceived sense of humor was positively correlated with people's job satisfaction.
What is Causation?
The statement that A caused B can be viewed as suggesting that when A is manipulated it results in an increased likelihood of a change in B. Thus, for example, we may observe a difference in the averages between an experimental group and a control group when A is manipulated in an experiment.
Single versus Multiple Causation
There may be different types of causes. I think we can make a distinction between single causation and multiple causation. Single causation implies that a variable is sufficient: it can influence another variable by itself. In contrast, multiple causation can be conceptualized as a combination of variables that are sufficient as a group, but none of the variables are sufficient individually.
References
Decker, W. H. (1987). Managerial humor and subordinate
satisfaction. Social Behavior and Personality, 15, 225-
232.