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The relationship between variables is one of the most useful patterns in industrial data analytics applications. For example, we are often interested in predicting a particular variable of interest, which is referred to as the response variable, based on available input information represented by a number of variables that are referred to as the predictor variables. In this situation, the relationship between the response variable and the predictor variables can help identify the most important predictors. Plotting of two variables can also be used to detect redundant variables and outliers in a data set. Depending on the types of variables being compared, different plots can be used to study the relationship between the variables.