Linear correlation plots are often used in conjunction with linear slope, linear intercept, and linear residual standard deviation plots. A linear correlation plot could be generated intially to see if linear fitting is a fruitful direction. If the correlations are high, this implies it is worthwhile to continue with the linear slope, intercept, and residual standard deviation plots. If the correlations are weak, a different model needs to be persued.

In some cases, you might not have groups. Instead you have different data sets and you want to know if the same correlation can be adequately applied to each of the data sets. In this case, simply think of each distinct data set as a group and apply the linear slope plot as for groups.

This linear correlation plot shows that the correlations are high for all groups. This implies that linear fits could provide a good model for each of these groups.

• Vertical axis: Group correlations
  
• Horizontal axis: Group identifier
  

1. Do you get linear relationships across groups?
2. Is the strength of the linear relationships relatively constant across the groups?