Correlation v. Causation
Correlation
• RELATIONSHIP b/w the
variables
• EX:?????
Causation
• CAUSE & EFFECT (X  Y) –
direct relationship
• EX: smoking/lung cancer
Correlations
Correlational studies use
statistical techniques to
measure the relationships
between variables
• Positive correlation: Both
variables go in the same
direction – up OR down
– EX: Studying & grades
• Negative correlation: The
variables go in opposite
directions (more of X
correlates with LESS of Y)
– EX: working out & weight
• http://www.correlated.org/
189
• Correlational Coefficient
 a # that measures
how strong a correlation
is (-1 to +1)
• Anything below 0 = neg;
above = pos (0 = no
relationship)
• The farther from 0, the
stronger the cor is in
either direction: -.84 is
stronger than .12
• Absolute value = distance
from 0 in either direction
Using Correlations (or Not)
Advantages
Disadvantages
• Simple to do & understand
• 90% of research = survey-based
• Sometimes can allow us to study
things that cannot be
manipulated
EX: teen TV & sex life
• They DO NOT show cause &
effect
– EX: murder rate & ice cream
• The third variable issue (CVs)
• The directional issue – don’t
know which direction the
correlation is in (don’t know
whether it was the chicken or
the egg)
– EX: auto workers & living in
Detroit
Sample Problem
• Dr. Durant wanted to test how people’s happiness
affected their self-esteem. He picked the first 50
people that walked into Target on a Saturday and
gave them hugs. Then he gave them a questionnaire
that asked how they felt about themselves. Dr.
Durant then went over to Wal-Mart and gave out
questionnaires to the first 50 people he saw. The
people at Target reported a higher level of selfesteem on their questionnaire than those at WalMart. Dr. Durant concluded that happiness causes
higher self-esteem.