Correlation is a statistical measure (expressed as a number) that describes the size and direction of a relationship between two or more variables. For example, the number of crimes (per capita) is related to the number of police officers in a given area. When more police officers are on patrol, crime tends to be lower and, when fewer police officers are present, the crime rate usually increases. Consequently, the number of police officers and the crime rate have a strong negative correlation.
A correlation between variables, however, does not automatically mean that the change in one variable is the cause of the change in the values of the other variable. Correlation as a statistic cannot explain why or how the relationship between two variables, x and y, exists; only that it does exist.
Causationgoes a step further than correlation by indicating that one event is the result of the occurrence of the other event; i.e. there is a causal relationship between the two events. That is, a change in the value of the x variable will cause a change in the value of the y variable.