Correlation vs Causation2

Association vs causation


Table of Contents

What is Association?

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.

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What is Causation?

Causation is defined as the relationship between two variables where one variable affects another. Causation is detected when there is an increase or decrease in the value of one variable as a result of the value of another present variable. 

Example: if you work for extra hours a day, your income is likely to increase. This means, one event (extra hours) is causing an effect on another event (income). This is a causal or cause-effect relationship.

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Association and Causation difference

Although, it does not always have to mean that association is caused by causation. Association can arise between variables having causation or those not having causation. 


  • The summer season causes an increase in the sales of ice cream. 

In this statement, the variables “Summer” and “sales of ice cream” have a causal association. As the summer season causes the sales of ice cream to increase, we can say that one variable causes an effect in another variable and also the both of them are dependent.

  • There is an increase in the sales of AC and ice cream.

In this statement, there is an association as “Summer season” is a common cause for the increase in both sales of AC and ice cream. But there is no causation as to both variables “sales of AC” and “sales of ice cream” have no cause-effect relationship between them and none of them affects the other. 

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