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Understanding Correlation vs. Causation: Unraveling Relationships Between Variables

This article explores the fundamental difference between correlation and causation in research. It defines correlation as a statistical measure indicating the relationship between two variables, including positive and negative correlations with real-world examples like smoking and lung cancer. Readers will learn about the correlation coefficient, how to interpret its strength, and the limitations of correlational studies, particularly the third variable issue and directional ambiguities. The article highlights both the advantages and disadvantages of using correlations in research while illustrating these concepts with pertinent examples.

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Understanding Correlation vs. Causation: Unraveling Relationships Between Variables

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  1. Correlation v. Causation Correlation Causation CAUSE & EFFECT (X  Y) – direct relationship EX: smoking/lung cancer • RELATIONSHIP b/w the variables • EX:?????

  2. 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

  3. 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

  4. Using Correlations (or Not) Advantages 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 • 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

  5. 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.

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