Understanding the difference between Correlation and Causation is critical for anyone who engages in data analysis and assessment of implications to further a set of recommendations. Likewise, senior executives need to understand the difference when evaluating recommendations and the supporting data.
- Correlation simply indicates a possible relationship between two factors. For example, Bank Marketing professionals will suggest that there is a Correlation between Brand Marketing and increase in the number of new customer relationships. After all, larger marketing spend usually results in increase in number of customers.
- Causation, on the other hand, indicates that one factor has a direct & measurable positive or negative impact on another factor. For example, large marketing spend has a direct & measurable impact on higher Bank costs. The more the marketing department spends, the higher the costs are. Causation, however, is not proven to exist between Brand Marketing and the growth in the number of customer relationships – as there are a large number of other factors that may have a much more important influence (for example – promotional rates, discounts, external factors beyond any one Bank’s control, etc.).
- It is essential to understand that Correlation does not imply Causation … that is, just because two factor are related in some way does not mean that one factor influences the other. For example, larger marketing budgets may be correlated to profitability but there is no Causal relationship between these factors. That is, higher marketing budgets do not necessarily increase Bank profitability — there are many other factors that have a direct relationship / impact on profitability.
To help understand this very important concept, SEOMOZ, a SEO (search engine optimization) software company, recently published an infographic entitled Correlation vs Causation, which is reproduced below.
Created by SEOmoz (Copyright ©2011).
Serge Milman
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