{domain:"www.qualitydigest.com",server:"169.47.211.87"} Skip to main content

User account menu
Main navigation
  • Topics
    • Customer Care
    • FDA Compliance
    • Healthcare
    • Innovation
    • Lean
    • Management
    • Metrology
    • Operations
    • Risk Management
    • Six Sigma
    • Standards
    • Statistics
    • Supply Chain
    • Sustainability
    • Training
  • Videos/Webinars
    • All videos
    • Product Demos
    • Webinars
  • Advertise
    • Advertise
    • Submit B2B Press Release
    • Write for us
  • Metrology Hub
  • Training
  • Subscribe
  • Log in
Mobile Menu
  • Home
  • Topics
    • 3D Metrology-CMSC
    • Customer Care
    • FDA Compliance
    • Healthcare
    • Innovation
    • Lean
    • Management
    • Metrology
    • Operations
    • Risk Management
    • Six Sigma
    • Standards
    • Statistics
    • Supply Chain
    • Sustainability
    • Training
  • Login / Subscribe
  • More...
    • All Features
    • All News
    • All Videos
    • Contact
    • Training

More to Beware About Tukey Control Charts

Answers to questions asked

Donald J. Wheeler
Mon, 09/09/2013 - 15:50
  • Comment
  • RSS

Social Sharing block

  • Print
Body

Last month’s column, “Beware the Tukey Control Chart,” generated several questions of a fundamental nature that deserve expanded answers. These questions and their answers will be considered here.

ADVERTISEMENT

Interquartile ranges

The Tukey control chart uses the interquartile range or IQR to characterize dispersion. One statistician wrote that he had found the IQR to be useful, especially in the presence of outliers. While he is right in saying that the IQR is less sensitive to outlying data points than is the global standard deviation statistic, this does not make it an appropriate measure of dispersion for a process behavior chart. The problem with the IQR is that it is a global measure of dispersion, i.e., it uses all of the data in the computation. As a global measure of dispersion it makes an implicit assumption that the data are homogeneous. This assumption is a distinct problem when you are examining the data for evidence of a lack of homogeneity, which is the purpose of a process behavior chart.

 …

Want to continue?
Log in or create a FREE account.
Enter your username or email address
Enter the password that accompanies your username.
By logging in you agree to receive communication from Quality Digest. Privacy Policy.
Create a FREE account
Forgot My Password

Add new comment

Image CAPTCHA
Enter the characters shown in the image.
Please login to comment.
      

© 2025 Quality Digest. Copyright on content held by Quality Digest or by individual authors. Contact Quality Digest for reprint information.
“Quality Digest" is a trademark owned by Quality Circle Institute Inc.

footer
  • Home
  • Print QD: 1995-2008
  • Print QD: 2008-2009
  • Videos
  • Privacy Policy
  • Write for us
footer second menu
  • Subscribe to Quality Digest
  • About Us
  • Contact Us