BACKGROUND
1. CORRELATION
Correlation means that two variables (sets of data) have some
type of association with each other, such that as one variable
increases, the other also increases (a positive correlation), or
decreases (a negative correlation).
2. CAUSE AND EFFECT
It is tempting to assume that when two variables are positively
correlated that one causes the other (i.e., the variables have a
"cause and effect" relationship, but this is not always the case.
The purpose of today's lecture is learn how to establish cause
and effect relationships from correlations and why this can be
a difficult task.