To draw a box plot, click on the вЂ™GraphicsвЂ™ menu option and then вЂBox plotвЂ™. Method 2: Box PlotДЄ box plot is the graphical equivalent of a five-number summary or the interquartile method of finding the outliers.

If such a value does exist in your dataset, sorting will easily help you identify it. If we were to change the last (maximum) value to, say, 50,000, it becomes an outlier since it is now a very high value as compared to its previous observation (14,500) (We are replacing this value because we want to demonstrate the process, you donвЂ™t have to replace the value in your data). give you a visual overview of how a variableвЂ™s values increase and whether a few extreme values exist in isolation. Sorting and inspecting will only serve to fulfill this part: i.e. In this case, the price variable appears to have no extreme values. The edit command opens the dataset for you to inspect and edit. LetвЂ™s sort the price variable (in ascending order) to see how outliers can affect it.

We start this by loading our dataset of choice, which in this case will be StataвЂ™s built-in auto dataset: sysuse auto.dta Method 1: Sorting the Data Identifying and Finding Outliers in Your Data only one variable is affected by the presence of outliers. These are outliers that pertain to only one variable in the dataset i.e. This article will only cover univariate outliers. Whether they are treated or not is something that the researcher decides based on the context and setting of their research. The meaning and interpretation of the term вЂoutlierвЂ™ may change depending on the type of data, the researcherвЂ™s objective, and the research setting. Put simply, an outlier is a value/observation in a dataset that is either extremely high or extremely low as compared to other values/observations in a given dataset. This article will delve into what outliers are, how we can identify outliers in Stata, and finally, how they can be treated in Stata.

Stata winsorize