If one variable causes a second variable, they should correlate (have a real relationship). Causation implies correlation.
However, two variables could be associated without having a causal relationship. For example, such a spurious relationship (apparent, but not truly causal) could occur because both the supposed independent variable and the supposed dependent variable are caused by a third variable. The apparent correlation between ice cream consumption and the number of assaults occurs statistically because the hot temperatures of summer cause both ice cream consumption and assaults to increase. Thus, correlation does NOT imply causation.
Recall that causes are called INDEPENDENT VARIABLES. If one variable truly causes a second, the cause is the independent variable.
Independent variables are often also called explanatory variables or predictors.
Effects are called DEPENDENT VARIABLES. We explain what has caused dependent variables.
Dependent variables are also sometimes called outcome or criterion variables.
Two variables may be associated but we cannot designate cause and effect. These aresymmetric relationships. In asymmetric relationships, we CAN designate cause and effect.
EXAMPLE: Married people average better mental health than unmarried people. However, we have evidence that marriage promotes mental health AND ALSO that mentally healthy people are more likely to marry. Thus, we can't clearly and unambigously designate cause and effect. This is a symmetric relationship.
http://edf5481-01.fa01.fsu.edu/Guide2.html 
Columbus Townhall > Forum > Politics > National > Science and Environment (Moderators: Peter, CTH Public Relations)
Topic: Global Warming Watch
