pts and Applications of Info however, it is not uncommon to see such use in the news media. An example is shown below. Divorce rate in Maine correlates with Per capita consumption of margarine Correlation: 99.26% (r-0.992558) 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 4.95 per 1,000 BIDS 4.62 per 1,000 Divorce rate in Maine Margarine consumed 4.29 per 1,000 3.96 per 1,000 2165 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 Margarine consumed - Divorce rate in Maine tylervigan.com Data sources. National Vital Statistics Reports nt of Agriculture Here we see that, at least visually, there appears to be a relation between the divorce rate in Maine and the per capital consumption of margarine. Does this imply that all married couples in Maine should immediately stop using margarine in order to stave off divorce? Common sense tells us that is probably not true. This is an example of a spurious correlation in which there appears to be a relation between the divorce rate and margarine consumption but, it is not a causal link. The appearance of such a relation could merely be due to coincidence or perhaps another unseen factor. What is one instance where you have seen correlation misinterpreted as causation? Please describe. This serves as your initial post to the discussion (if you choose topic #1) and is due by