Stratification

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Stratification 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 impossible to see. This technique separates the data so that patterns can be seen.

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.

Stratification Procedure

  1. Before collecting data, consider which information about the sources of the data might have an effect on the results. Set up the data collection so that you collect that information as well.
  2. When plotting or graphing the collected data on a scatter diagram, control chart, histogram or other analysis tool, use different marks or colors to distinguish data from various sources. Data that are distinguished in this way are said to be “stratified.”
  3. Analyze the subsets of stratified data separately. For example, on a scatter diagram where data are stratified into data from source 1 and data from source 2, draw quadrants, count points and determine the critical value only for the data from source 1, then only for the data from source 2.

Stratification 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. The team member redrew the diagram, using a different symbol for each reactor’s data:

Stratification figure

Now patterns can 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 that are not circled, do not show that relationship. Something is different about reactor 1.

Stratification Considerations

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

Excerpted from Nancy R. Tague’s The Quality Toolbox, Second Edition, ASQ Quality Press, 2005, pages 485–487.

Create a Stratification Diagram

Stratification Diagram (Excel, 78 KB) – Analyze data collected from various sources to reveal patterns or relationships often missed by other data analysis techniques. By using unique symbols for each source, you can view data sets independently or in correlation to other data sets.

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