Why are correlation and causation important? In practice, however, it remains difficult to clearly establish cause and effect, compared with establishing correlation. smoking is correlated with alcoholism, but it does not cause alcoholism). smoking causes an increase in the risk of developing lung cancer), or it can correlate with another (e.g. Theoretically, the difference between the two types of relationships are easy to identify - an action or occurrence can cause another (e.g.

This is also referred to as cause and effect. there is a causal relationship between the two events. 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.Д¬ausation indicates that one event is the result of the occurrence of the other event i.e. If we consider the two variables 'price' and 'purchasing power', as the price of goods increases a person's ability to buy these goods decreases (assuming a constant income).Д¬orrelation is a statistical measure (expressed as a number) that describes the size and direction of a relationship between two or more variables. Two or more variables considered to be related, in a statistical context, if their values change so that as the value of one variable increases or decreases so does the value of the other variable (although it may be in the opposite direction).ДЇor example, for the two variables 'hours worked' and 'income earned' there is a relationship between the two if the increase in hours worked is associated with an increase in income earned. What are correlation and causation and how are they different?

Covariance rule for causality