Correlation vs Causation…

Correlation vs Causation


2 thoughts on “Correlation vs Causation…

  1. Suppose Congress cuts spending for the military and the unemployment rate rises in the US defense industry. Is there causation in this situation or an association between events?

    1. Hi Christian,

      Your question sounds straight-forward, but is somewhat more complex than that:

      1. Two or more variables are considered to be related, in a statistical context, if their values change so that as the value of one variable increases or decreases so does the value of the other variable (although it may be in the opposite direction, an inverse relationship).
      2. For example, for the two variables ‘defence spending’ and ‘unemployment rate’, there is a relationship between the two if the increase in defence spending is associated with an increase in ’employment rate’. If we consider the two variables ‘price’ and ‘purchasing power’, as the price of goods increases the ability (of a person, organisation or government) to buy these goods decreases (assuming a constant income).
      3. Correlation is a statistical measure (expressed as a number) that describes the size and direction of a relationship between two or more variables. A correlation between variables, however, does not automatically mean that the change in one variable is the cause of the change in the values of the other variable.
      4. Causation indicates that one event is the result of the occurrence of the other event, in other words, there is a causal relationship between the two events. This is also referred to as cause and effect.
      5. Theoretically, the difference between the two types of relationships are easy to identify — an action or occurrence can cause another (e.g. smoking causes an increase in the risk of developing lung cancer), or it can correlate with another (e.g. smoking is correlated with alcoholism, but it does not cause alcoholism). In practice, however, it remains difficult to clearly establish cause and effect, compared with establishing correlation.
      6. In summary: One could possibly prove a correlation between decreased defence spending and a rise in the unemployment rate, proving causation would be more problematic. Possible results of reduced defence spending could be: increased unemployment rate; workers moving to another part of the business (in similar/different role); workers moving to another industry; and/or workers taking early retirement. Also, reduced defence spending could be a result of business efficiencies or cheaper goods/products, without any reduction in manpower levels. Finally, businesses may have taken decisions on manpower levels independent of defence spending (in correlation terms 0, indicating there is no relationship between the variables).

      Hope this helps.

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