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Correlation or Causation

The ideal method for studying science is to study the direct influence of one condition on another in the experiments where all other possible causes for variation have been eliminated. Many a times these cause of variation are beyond control. We can calculate the degree of variation between two variables by the well known methods, but these only give the resultant of the various connecting paths of influence.

When occurrence of one action can cause the occurrence of other, it is termed as causation (for example smoking leads to skin cancer), while when two actions are correlated, they are termed as correlation. (For example, smoking is often correlated with cancer). Many studies are designed for testing a correlation, but only suggest the reasons for correlation. For example a study on girls watching soap disorders can have eating disorders also [people to incorrectly assume that the watching of soap operas gives girls the eating disorders. Therefore in general concept, it becomes difficulty to establish the causality which can occur between two correlated events or observance. But there are many statistical tools for establishing a statistically significant correlation.

The correlated occurrences often occur due to a common cause. For example, the common fact of red hair being associated with blue eyes is deduced fro the common genetic specifications coding for both. A correlation can also be observed with causality behind it. As an example, the fact that cigarette smoking not only correlates with lung cancer but also leads to its occurrence is established. But to establish the cause we have to rule out the possibility that smokers only live in urban areas having more population as well as any other possible explanation for the calculation which is observed. In many cases, the citation of one action leading to other is obvious and in many cases it is unclear. For example in the case of soap opera watching anorexics, the hypothesis that the television is causing the problem cannot is excluded. But for getting a convincing model for causality we have to do additional research.

Thus, for establishing causality the controlled study is helpful. The controlled study has two groups of people which are capable in almost every possible way which are given two sets of experiences and the outcome is compared. When the two groups have substantially different outcomes, then the different experiences are behind the different outcomes.

Because there are obvious ethical limitations to controlled studies, the epidemiological studies are highly important. Their are studies which conducted for large groups of people which are followed over time and then their behavior and outcome is observed.

The correlation can be established unless the effects are notable in extreme and no reasonable explanation is found challenging causality. In case the stakes are high, people do jump to casual conclusions. When the cases involve public suspicions of environmental and chemical pollution, it becomes doubly true. For example, a lot of publicity has been given to the relationship between environmental pollution and chemicals. Two events which occur in close proximity should not be seen as one causing the other, even when it makes perfect sense.

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