Image: Yale: Scatterplot
A scatter plot identifies a possible relationship between changes observed in two different sets of variables. By presenting the data in a clear manner, it provides a visual and statistical means to test the strength of a relationship between two variables.
Scatter plots can be effective in measuring the strength of relationships uncovered with a fishbone diagram.
A very basic description of scatter plots follows; for more detailed help on construction and interpretation, consult the resources listed below.
Creating a Scatter Plot
- Collect at least 50-100 paired samples of data that you think might be related, and build a data spreadsheet
- Draw the horizontal and vertical axes of the diagram
- Plot the data points on the diagram (if you have created your spreadsheet in MS Excel, you can use the program to build a scatter plot with your data)
Interpreting a Scatter Plot
Many levels of analysis can be applied to the diagram. You might find it helpful to consult a statistical process control guide or other texts for assistance with analysis, in order to ensure you're correctly identifying a positive or negative correlation (or absence thereof).
It's important to note that scatter plots show correlation between two variables, from which causation may or may not be inferred.
|American Society for Quality: Scatter Diagram|
|NIST/SEMATECH e-Handbook of Statistical Methods: Scatter Plot|
|Miller, Moore, Richards and McKaig: A Screening Survey to Assess Local Public Health Performance (PDF: 1MB / 6 pages)|
|Public Health Memory Jogger
If you belong to a local health agency in Minnesota and would like a Memory Jogger free of charge, please contact the QI Unit.