Purpose: The purpose of the QQ plot is to test for normal distribution in a column of data. Many predictive models require that the data be normally distributed. If it is not, then the model will not work well. This plot can help a user determine if their data is normally distributed and whether or not it should be fed into a given predictive model.
Inputs:

Data table
 Column
Limitations:
 Can only run one column at a time
Prep:
Steps to Run:
 Go to the Tools menu
 Select the Data Science option
 Select the QQ plot option
 Enter the data table and the column name the analysis should be performed on
Outputs:
 The output is a single scatter plot visualization.
 Normal Quantiles are on the x axis and the Sample Quantiles are on the y axis.
Interpretation:
 If the data is normally distributed, it will fall along the line in the plot.
 If the data is not normal, then you can apply transformations, select a subset of data, or remove outliers.
Data Science Toolkit  QQ Plot from Ruths.ai on Vimeo.