causation

Examples of causation in the following topics:

• Correlation and Causation

  • In the scientific pursuit of quantitative prediction and explanation, two relationships between variables are often confused: correlation and causation.
  • Causation refers to a relationship between two (or more) variables where one variable causes the other.
  • It is at this point that a simple yet noteworthy phrase should be introduced: correlation is not causation.
  • If you look back at the three criteria of causation above, you will notice that the relationship between ice cream consumption and crime meets only one of the three criteria (they change together).
  • This diagram illustrates the difference between correlation and causation, as ice cream consumption is correlated with crime, but both are dependent on temperature.

• Causation

  • The concept of causation is a complex one in the philosophy of science.
  • Since a full coverage of this topic is well beyond the scope of this text, we focus on two specific topics: (1) the establishment of causation in experiments and (2) the establishment of causation in non-experimental designs.
  • It is almost a cliché that correlation does not mean causation.
  • The main fallacy in inferring causation from correlation is called the "third-variable problem" and means that a third variable is responsible for the correlation between two other variables.

• Introducing observational studies and experiments

  • In general, association does not imply causation, and causation can only be inferred from a randomized experiment.

• Correlation is Not Causation

  • The conventional dictum "correlation does not imply causation" means that correlation cannot be used to infer a causal relationship between variables.
  • The conventional dictum that "correlation does not imply causation" means that correlation cannot be used to infer a causal relationship between the variables.
  • The assumption that correlation proves causation is considered a "questionable cause logical fallacy," in that two events occurring together are taken to have a cause-and-effect relationship.

• Analyzing Data and Drawing Conclusions

  • But they must be cautious not to mistake correlation for causation.
  • To better understand the difference between correlation and causation, consider this example.
  • This relationship is a correlation and it does not necessarily imply causation.
  • It is important to remember, however, that correlation does not imply causation; in other words, just because variables change at a proportional rate, it does not follow that one variable influences the other .
  • This mock newscast gives three competing interpretations of the same survey findings and demonstrates the dangers of assuming that correlation implies causation.

• Descriptive and Correlational Statistics

  • Correlation does not necessarily prove causation.
  • This is different than causation, where one variable is found to cause the other.
  • Only scientific experiments can prove causation.

• Facts, Information, Knowledge and Wisdom

  • Knowledge implies an understanding of the nature of relationships (system of causation) among the facts and information.

• Congenital Defects

  • A congenital disorder, or congenital disease, is a condition existing at birth and often before birth, or that develops during the first month of life (neonatal disease) regardless of causation.
  • Congenital disorders vary widely in causation and abnormalities.

• Explanatory and response variables

• Correlational Research

  • Unlike experimental studies, however, correlational studies can only show that two variables are related—they cannot determine causation (which variable causes a change in the other).
  • In psychological research, it is important to remember that correlation does not imply causation; the fact that two variables are related does not necessarily imply that one causes the other, and further research would need to be done to prove any kind of causal relationship.
  • Always remember that correlation does not imply causation.
  • Only experimental research can determine causation.