Determining Causality: Defined and Explored

## Determining Causality: Defined and Explored

Identifying where influence exists and the direction of that influence

### Mistaken causal inference: It could happen you

Inferring causality between variables, ideas, or events when none exists is a serious but common error in judgment (Haig, 2003). If we are to reason effectively, we must make sound judgments about the connections between ideas, and this includes whether there is a cause-effect relationship between things. Teaching students to be skeptical about causal claims can help them to become better-informed consumers of research, ideas, and even products.

### The troubled relationship between correlation and causation

Students often make the mistaken assumption that when two events occur together or in sequence -- in other words, when some sort of correlation exists between the two variables -- that change in one variable causes change in the other (Harcum, 1988; Jungwirth & Dreyfuss, 1992).

Halpern (2003) identified a few types of correlation that students often use to erroneously infer causality: illusory correlations, spurious correlations, and accidental correlations.

• Illusory correlations are based on an individual's preconceived notions or beliefs which lead one to look for associations between variables that confirm those.
• Accidental correlations have no logical connection between them, an amusing example of which is the findings by Höfer, T., Przyrembel, H., and Verleger (2004) that for 25 years, the stork population in Berlin, Germany has correlated positively with the number of babies delivered outside of hospitals.
• Finally, spurious correlations are correlations between two variables that are actually caused by a third variable (a.k.a. the "third variable problem").

Above is an illustration of a classic spurious correlation. How can one explain the nearly perfect positive correlation between the number of churches in any given city and the number of bars? Do churches give rise to bars? Do bars give rise to churches? The answer, of course, is that a city's growing population gives rise to both.  Introducing this phenomenon by way of a classroom activity can be particularly effective in helping students refine their causal thinking.

### Teaching causal reasoning

Claims that certain things cause others are very common in today’s world, and it is important to help students acquire a certain sense of causal skepticism.  A fun twist to put on any causation activity in the classroom is to ask students to first make an argument for causation to run one direction, and then ask them if evidence can be found for causation to run the opposite direction

Advertisements and articles in the media can provide rich opportunities to challenge students to think critically about what evidence exists or does not exist for the causal reasoning they present (Connor-Greene, 1993). For a more nuanced consideration of causal influences, some teachers assign writing projects that engage the creative energy of students and their peers to help them understand that causality is not an abstract process that happens in a laboratory, but is important to everyone’s daily life.

Activities like these can open students’ minds to the importance of experimental design, which is the tool often used to make stronger determinations of causality (Adams, 2003). By adding an experimental design step onto the end of a cause/effect class exercise like "after this, therefore because of this," one can help students take the next intellectual step from simply being skeptical of causal claims to identifying how one would specifically test those claims.

References

Adams, D.S. (2003). Teaching critical thinking in a developmental biology course at an American liberal arts college. International Journal of Developmental Biology, 47, 145-151.

Connor-Greene, P.A. (1993). From the laboratory to the headlines: Teaching critical evaluation of press reports of research. Teaching of Psychology, 20(3), 167-169.

Haig, B.D. (2003). What is a spurious correlation? Understanding Statistics, 2(2), 125-132.

Halpern, D.E. (2003). Thought and knowledge (4th Edition). Lawrence Erlbaum Associates: Mahwah, New Jersey.

Harcum, E.R. (1988). A classroom demonstration of the difference between correlation and causality. Perceptual and Motor Skills, 66, 801-802.

Hatfield, J. (2006). Avoiding confusion surrounding the phrase " "correlation does not imply causation." "Teaching of Psychology, 33(1), 49-51.

Hö "fer, T., Przyrembel, H., & Verleger, S., (2004).  New evidence for the Theory of the Stork. Paediatric and Perinatal Epidemiology, 18(1), 88-92.

Jungwirth, E., & Dreyfuss, A. (1992). After this, therefore because of this: One way of jumping to conclusions. Journal of Biological Education, 26(2), 139-142.

Spears, R., Eiser, J.R., & Van Der Pligt, J. (1987). Further evidence for expectation-based illusory correlations. European Journal of Social Psychology, 17, 253-258.