As part of our quest to understand the Algorithm, we do a lot of correlation analysis here at SEOmoz. We tend to dive right into the deep end, so I thought it might be a good time to take a step back and talk about the absolute basics of correlation, including some warnings about causation. We’ll often say (and hear) the fallback phrase – “correlation does not imply causation”, but people rarely dig into what that means.

To make this experience as pleasant as possible for the math-phobic, I drew you a picture. I’d like to introduce the world’s first Mathographic. Ok, it’s probably not the world’s first, and it’s really just an infographic, but give a guy credit for trying to keep you entertained.

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<div style="width:604px;"><div><a target="_blank" href="https://moz.rankious.com/_moz/blog/correlation-vs-causation-mathographic" ><img width="600" height="1658" alt="Correlation vs. Causation (A Mathographic)" src="https://moz.rankious.com/_moz/img_uploads/correlation-vs-causation-sm.gif" style="border: #cccccc 1px solid; padding: 1px;" /></a></div><div style="text-align:right; font-size:11px; margin-right: 5px;">Created by <a href="https://moz.rankious.com/_moz/blog/correlation-vs-causation-mathographic" >SEOmoz</a> (Copyright ©2011).</div></div>

Obviously, our actual studies get a lot more complex than this, but everything has to start somewhere. If you’re interested in more advanced topics on correlation, here are a few references worth checking out:

• Correlation and Dependence (Wikipedia)
• Stastistical Signifcance of Correlations (SUNY)
• Spearman’s Rank Correlation (U. Delaware)
• Non-linear Regression (Graphpad)
• Some Correlation Humor (xkcd)

Are there any other correlation-related topics you’d like to hear more about on the blog? Are there analyses that you’re interested in within the broader realm of SEO and social media? Let us know in the comments.