Difference between Error and Residual

What is the difference between Error Term and Residual?

These days Analytics world is full of Non-statisticians. They do the suitable blend of Business and Statistics and prepare palatable deliverable. But being from a non statistics background, sometimes they mix up the terminologies.
One of the examples is Error and Residual. Most of us think that these are same and especially in context of Linear regression, these Non-statisticians analysts use this two terms interchangeably. However, there is a difference. Let's have a  closer look ...



The error term is the difference between the observed value for the dependent variable and its theoretical value, while a model is applied on overall population. We don't actually calculate it.

Residual is the practically calculated term during modeling exercise; It is the difference between the actual value in the sample and predicated value in the sample.





Residual is related to sample and Error-term is related to population.

In exact words residual while extrapolated on population, it gives error.


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