Difference between Association and Causation

Association is a statistical relationship between two variables. This relationship tells you nothing but the value on one variable when you are known of the value of the other. These variables or measured quantities are dependent. 

Association is similar to correlation due to their intent of determining the patterns of variance in two or more terms. But correlation works ahead by using correlation coefficient which is used to measure the degree to which the association of the variables depends on some patterns. 

Correlation tends to define either linear or non-linear associations between the vehicles. The linear association is nothing but a simple linear relationship between the variables. There are various measures of association that infer the presence or absence of association in a given dataset. 

Example: there is an association between the number of increased sales of AC and the number of increased sale of ice cream in an area. But there is definitely no causal relationship.