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• Simple to do & understand• 90% of research = survey-based• Sometimes can allow us to study

things that cannot be manipulatedEX: teen TV & sex life

Disadvantages• 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 self-esteem on their questionnaire than those at Wal-Mart. Dr. Durant concluded that happiness causes higher self-esteem.