RDM: Correlation vs Causation
When making a decision, we should always ensure that we are not confusing correlation with causation. This happens more often that we think it does, and even some newspapers are susceptible to interchanging the two in their articles. This, in some cases, can be extremely controversial, as we don't know their underlying motives. For example, many newspapers have written about studies that apparently show people who eat breakfast are less obese. This essentially points towards causation, however, it is more likely that in the given sample, this was just a mere correlation between the two things. Informed readers always think critically, and they might identify this as a deliberate ploy from the breakfast cereal companies in getting more people to buy their product.
The most that such articles can do is state that they found a correlation between eating breakfast and less obesity. And that even though, they APPEAR to be related, we cannot be sure. Hence, the statement that "people who eat breakfast are less obese" might be true or it might not be. We simply don't have enough information to be able to confidently support or reject that assertion.
The significance of this is that we should always be careful in judging whether there is a causal relationship between two things or whether its just simple correlation before making a decision based on it. In the case of a confirmation bias, this becomes even more important. We have to resist from blindly using data that confirms our idea, as it may only be showing the correlation between two completely unrelated things.