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**Box Plot**

A box plot shows the distribution of data. It is useful in visualizing skewness in data.

**How to Read a Box Plot**

**Interpretation**

**Normal Distribution or Symmetric Distribution :**If

**a box plot has equal proportions around the median, we can say distribution is symmetric or normal.**

**Positively Skewed :**For a distribution that is positively skewed, the box plot will show the median closer to the lower or bottom quartile.

A distribution is considered "Positively Skewed" when mean > median. It means the data constitute higher frequency of high valued scores.

**Negatively Skewed**: For a distribution that is negatively skewed, the box plot will show the median closer to the upper or top quartile.

A distribution is considered "Negatively Skewed" when mean < median. It means the data constitute higher frequency of low valued scores.

**Outlier**: If a value is higher than the 1.5*IQR above the upper quartile (Q3), the value will be considered as outlier. Similarly, if a value is lower than the 1.5*IQR below the lower quartile (Q1), the value will be considered as outlier.

**Note**: IQR is interquartile range. It measures dispersion or variation. IQR = Q3 -Q1.

Thanks a lot for the wonderful explanation.This site is very useful and I love this. Please help us to learn more on basic and advanced statistical techniques.

ReplyDeleteThanks in advance.

Thank you so much for your appreciation!! Check out this article - Cluster Analysis using SAS

Deletehttp://www.listendata.com/2014/10/cluster-analysis-using-sas.html

Thanks for sharing above information. This really helped me indeed.

ReplyDeleteI believe box plot is the best way to identify outliers in our linear regression model.

To create box plot I mention plot in options in proc univariate SAS, do you know any other procedure or option by which we can create box plot and to make it more presentable.

Glad you found it useful. Yes, you can customize box plot by using PROC BOXPLOT procedure.

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