Identifying outliers

An outlier is a data point in your dataset that is out of place or doesn't fit well with other data. For example, we might collect data about our daily revenue and see that each day we consistently have $1,000 in total sales. If we then have a day where our daily revenue is about $6,000, then that would be an outlier if the daily revenue then goes back down to $1,000. Outliers can be either positive or negative; in fact, they are just any deviation from a typical or expected result. It is important to identify and deal with outliers because they can cause problems when we try to make business decisions as they skew decisions; when outliers have been properly identified, they will help ensure the higher accuracy of insights gained from your data. You can define your calculations on what an outlier is. You can create measures to define what would be considered anomalous in your dataset.

Math

In mathematics, outliers are often defined as being more than...