Correlation VS Causation

As it is known to all , that the scientific thinking is a crucial method for people to analyse a series of phenomena to get the essence , finally conclude the theory . There are 6 principles of scientific thinking : Ruling out rival hypothesis, correlation VS. Causation , falsifiability , replicability , extraordinary claims, and Occurs' Razor. Today , I would like to pick "Correlation VS. Causation" to analyse.

A correlational study is one that utilizes the correlation coefficient to show a relationship between two variables . A correlation exists when two variables are related to each other , and the range of possible correlations is from +1.0 to -1.0 , the greater the correlation coefficient is from zero, the stronger the relationship.

As far as I am concerned , the so-called "correlation" is kind of method to reflect the intensity of relationship between these two variables , this method effectively concrete nonfigurative relationship into actual number , as a result , it is more obvious for experimenter to identify . According to the range of correlation , we can divide " correlation " into two part : positive correlation and negative correlation . The difference between these two are the quality of the result brought by one variable to the other one . The good result refer to "positive" correlation , and bad result refer to "negative" correlation. For example , if the government decide to plant more trees on the side of the road , then our living environment will be better , this is " positive correlation" . What's more , if a student did not do his homework on time , then his parents are really mad at him , this is an example of "negative correlation".

There is another concept really similar to "correlation", that is "causation" . From the literal meaning we can see the "cause" inside , which elaborate the meaning of this word : there are two variables , and on variable is a reason of the other , in another word, one variable is a result of the other.

People are easily confused by these two things because some of them can not identify if there is really exist causation relationship between two things or only have ordinary relationship.

There are some link of websites which can explain it more specifically:
http://stats.org/in_depth/faq/causation_correlation.htm

http://en.wikipedia.org/wiki/Correlation_does_not_imply_causation