Correlation v. Causation

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Presentation transcript:

Correlation v. Causation RELATIONSHIP b/w the variables EX:????? 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 self-esteem on their questionnaire than those at Wal-Mart. Dr. Durant concluded that happiness causes higher self-esteem.