Causation vs. Correlation –


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Whether you are a student, a lawyer, a marketing specialist, a programmer or an online entrepreneur, knowing the different between causation and correlation is quite important, especially because so many people get confused with it.

Want a practical example of how this can affect your website or blog? Just think about SEO. Great part of optimizing a site for search engines is understand how changes you make on your site affect your rankings, but you need to separate correlation and causation of factions, else you’ll never understand what is going on.

Last week I came across an interesting infographic on this topic, and I figured it would be nice to spread it around. Here’s the link on SEOMoz: Correlation vs. Causation (A Mathographic).

If you are in a hurry, though, here’s what you need to know about those concepts:

  1. Correlation is a concept from statistics that measures the relationship between two things. A positive correlation means that when one thing goes up, the other goes too. A negative correlation is the opposite, when one goes up, the other goes down.
  2. For example, when the demand for a certain product goes up, its price tends to go up as well, so there is a positive correlation between the two things.
  3. Causation, on the other hand, means that one thing will cause the other. For example, when you exercise the amount of calories you are burning per minute will go up, as the former is causing the latter.
  4. Correlation and causation can happen at the same time. In the example above about exercising, for example, there’s both correlation and causation in place.
  5. However, having a correlation doesn’t imply that you also have causation, and this is where most people get confused.
  6. For example, there is a positive correlation between the number of firemen fighting a fire and the size of the fire. However, this doesn’t mean that bringing more firemen will cause the size of the fire to increase (this is called reverse causation).

If you want to get a more in-depth analysis or read more examples check out Wikipedia’s page on Correlation and causation.


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