The best example I could find in differentiating between correlation and causation is explained in a graph published by gizmodo.com. The graphic shows a strong correlation between the market shares of the web browser internet explorer and the amount of murders in the United States. While I can understand where they are coming from by linking the data, this is a perfect example of where correlation does not necessarily imply causation.
However just to be safe, everyone should save lives and use Chrome. 
Oh this is gold. I think this really does show the difference between correlation and causation as it is clearly absurd that murder rates could in any way be linked to a decline in Internet Explorer use. Graphs like this remind me to be careful when looking at data displayed as such because of how misleading it can be (as long as it’s a bit more believable than this graph). On a tangential note, I did not know the U.S. murder rate was going down. That’s a bit of good news.
I like how you brought humor into analyzing correlation and causation. It really can help someone better understand the difference between the two. The thing with correlation, is that a lot of reports use the statistics from studies that show correlation but disregard that there was no causation showed. Especially with unlimited access to the internet and all the information you can get on the internet, it would be easy for any person to get fooled by reports that say two things are correlation like murder rates and Internet Explorer. If any normal person that wasn’t educated on the difference between correlation and causation, I’m sure they would be posting this link on their Facebook proclaiming this crazy discovery.