Something that has always been mind boggling to me is correlation versus causation and grasping the concept of it. The fact of the matter is that correlation does not imply causation. I've learned about this in math (probability and statistics) as well as in this class now and it still is a hard concept for me to grasp. What this phrase emphasizes is that two variables do not automatically imply that one cause the other. Often times we see this in news and in printed press, but a lot of the time news broadcasters and writers are wrong in doing so.
While I was reading an Enquirer recently, I stumbled upon an article that reminded me of this phenomenon. The title of it was"Eating Chocolate Protects The Heart". In the article, it talked about how consuming more chocolate can cut the risk of developing heart disease and stroke by about one third. This information was derived from the Cambridge University researchers who analyzed more than 100,000 people. They discovered that those who consumed the most chocolate were at an astonishing 37% lower risk of developing heart disease and a 29% lower risk of suffering a stroke. What the researchers forgot to analyze were the confounding variables- an extraneous variable in a model that correlates with both the dependent and independent variable. When researchers account for these variables,they avoid a false positive error. These researchers never did therefore this study throws off the facts.
Moral of the story is that Psychologists and other researchers are very careful when drawing conclusions of certain research and case studies. They have to be in order to deliver the correct information to the public. A lot of the time, news and media ignore these tactics and don't always properly inform the public. This information is hard to grasp, but hopefully I will come to better understand it.