How to Choose a Control Chart Using a Decision Tree

Jay Arthur
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A control chart decision tree can help you choose the right control chart based on the data (variable or attribute) and sample size. To save you time and headaches, the QI Macros control chart wizard can analyze your data and choose the right chart for you.

Click here to download a free SPC quick reference card with a Control Chart Decision Tree .

Many people struggle with choosing the right control chart. Use the decision tree above or the question and answer format below to select the right chart.

Select the Right Control Chart - Attribute vs Variable Data

Is the data for the control chart variable data?
(e.g., time, height, length, width, weight, money?) Yes No

Is the data for the control chart discrete or attribute data?
(e.g., number of people, complaints, defects, missed commitments, repair reports, etc.)? Yes No

Control Charts for Variable Data

Do you collect 2-10 samples of the data at the same time?
(e.g., length of five concurrent customer calls in a 60 person office? Use the XbarR Chart

Do you collect more than 10 samples of the data at the same time? Use the XbarS Chart

Control Charts for Attribute Data

Do you count the number of defects in a given product or service?
(e.g., defective splices in a cable or the number of mistakes in a typed letter?) Yes No

Number of Defective Units

Does the sample size vary from day to day?
(e.g., number of incorrect payment to vendors per day? Use the "p" Chart

Number of Defects Per Unit

Does the sample size vary from day to day?
(e.g., number defects in all service orders? Use the "u" Chart

• Download our Choosing the Right Control Chart quick reference card.
• For an explanation of why there are so many different types of control charts see our QI Macros formulas page.
• Control chart types
• QI Macros control chart wizard
• Choosing the right chart article with data example

The QI Macros contains all of the variable and attribute charts and the control chart wizard to choose the right chart for you.

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