# Correlation

Did you know that most statistics out in the media is deceiving? Most people think they have a pretty good idea about something if they look at charts or numbers. However, most data is skewed or made not be presented in the most accurate way possible. An example of data is correlation. Correlation is a number used to describe a graphical representation of a relationship between two variables. While its purpose is to give a statistical means of showing how two variables could be related, it does not mean that one variable causes another variable to happen. I see it often in classes and other places were people will use the word "cause" to describe a correlation. A scatter plot of the relationship between two variables does not include any underlying variable that may cause the relationship. So it is not technically correct to use the word "cause" when describing correlations.

I've taken statistics classes in high school and here at the U. In all classes, the teacher or professor would be very picky about our word choices when explaining data. It took some time to get used to thinking about data a certain way because usually the way data is presented can be deceiving and made to believe it is one way.

People like the convenience to link one cause to one reaction. However, in some cases this is far from the truth. Like you said there are multiple causes that go under the radar but are never measured.

I think that distinguishing correlation from causation is easy to talk about but hard to remember in everyday life. There are times when I am sure that my performance at work is making another worker slightly irritated. But how can I be sure that it isn't because of their ticket they got last night? I can sure see how hard it must be for scientists to avoid this instinct, even though it proves to be wrong so often.

We all know now that "correlation does not mean causation" but I can understand why most people in society don't realize that. It can be easy to assume causation relationships from correlation. Perhaps if you see a correlation between weather during a particular week VS. ice cream sales, you may see a strong correlation between the weather getting warmer and higher ice cream sales. Many would assume that the weather is causing the increase in ice cream sales, but you can not be sure. A third factor, such as an ice cream sale, or something could be causing the change. Even when things seem obvious you cannot assume correlation means causation.