OUTLIERS are the data records which are different from the NORMAL records in some of their characteristics. It is very important to first decide the characteristics of the normal records in order to detect the outliers. These records when used in ALGORITHMS or analytical systems can provide ABNORMAL results which may impact the analysis process. So, it is very important to detect the outliers to avoid such abnormalities.

We can detect outliers using tables or graphs by directly looking at them. As an example, let suppose there is table containing the Name and Age of few people and one of the rows representing a person contains Age as 500. So, we can easily analyse that value to be an invalid value as age can be 40,50 or 55 but it can’t be 500. So, we can predict the age but can’t sure about the exact value. This kind of detection is easy when we are dealing with a table with limited records but if the tables CONTAIN thousands of records, then it becomes impossible to detect the outliers.