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This last article introduces stratification, the act of sorting data, people, and objects into distinct groups or layers. It is a technique used in combination with other data analysis tools. When data from a variety of sources or categories have been lumped together, the meaning of the data can be difficult to see.

This series of articles presented the 7 Basic Quality Tools for Process Improvement used in the field. These are defined as instruments or techniques to support and improve the activities of quality management and improvement. ASQ has made available to the members and the public a huge amount of information on the "quality" body of knowledge (BOK). It is only meant to be a starting point, but oh so useful.

When to use stratification:

• Before collecting data;
• When data come from several sources or conditions, such as shifts, days of the week, suppliers, or population groups;
• When data analysis may require separating different sources or conditions.

Here are examples of different sources that might require data to be stratified:

• Equipment
• Shifts
• Departments
• Materials
• Suppliers
• Day of the week
• Time of day
• Products

Create a stratification diagram:
Read the full article on stratification then, pull-out a computer and use the following stratification template (or your own). This simple visual tool also allows you to analyze six categories of 20 points of data collected from various sources. It should reveal patterns or relationships often missed by other data analysis techniques and by using unique symbols for each source, you can view data sets independently or in correlation to other data sets.

In this example the ZZ-400 manufacturing team drew a scatter diagram to test whether product purity and iron contamination were related, but the plot did not demonstrate a relationship. Then a team member realized that the data came from three different reactors, so the team member redrew the diagram, using a different symbol for each reactor’s data. Now patterns could be seen — the data from reactor 2 and reactor 3 are circled. Even without doing any calculations, it is clear that for those two reactors, purity decreases as iron increases. However, the data from reactor 1 (the solid dots not circled) do not show that relationship so something is different about reactor 1.

Stratification Analysis Considerations:

• Survey data usually benefit from stratification.
• Always consider before collecting data whether stratification might be needed during analysis. Plan to collect stratification information.
• On your graph or chart, include a legend that identifies the marks or colors used.

§ This News post was adapted by J.P. Amiel, ASQ Senior, CQA ret., Web committee Chair, from content at ASQ's Quality Resources pages, which are excerpted and adapted from The Quality Toolbox, Second Edition, ASQ Quality Press

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ASQ References:

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